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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
1136 lines
163 KiB
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1136 lines
163 KiB
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<div class="title">/data/users/matthijs/github_faiss/faiss/IndexScalarQuantizer.cpp</div> </div>
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</div><!--header-->
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<div class="contents">
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<div class="fragment"><div class="line"><a name="l00001"></a><span class="lineno"> 1</span> <span class="comment">/**</span></div>
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<div class="line"><a name="l00002"></a><span class="lineno"> 2</span> <span class="comment"> * Copyright (c) 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="preprocessor">#include "IndexScalarQuantizer.h"</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 <cstdio></span></div>
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<div class="line"><a name="l00012"></a><span class="lineno"> 12</span> <span class="preprocessor">#include <algorithm></span></div>
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<div class="line"><a name="l00013"></a><span class="lineno"> 13</span> </div>
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<div class="line"><a name="l00014"></a><span class="lineno"> 14</span> <span class="preprocessor">#include <omp.h></span></div>
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<div class="line"><a name="l00015"></a><span class="lineno"> 15</span> </div>
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<div class="line"><a name="l00016"></a><span class="lineno"> 16</span> <span class="preprocessor">#include <immintrin.h></span></div>
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<div class="line"><a name="l00017"></a><span class="lineno"> 17</span> </div>
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<div class="line"><a name="l00018"></a><span class="lineno"> 18</span> <span class="preprocessor">#include "utils.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 "FaissAssert.h"</span></div>
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<div class="line"><a name="l00021"></a><span class="lineno"> 21</span> </div>
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<div class="line"><a name="l00022"></a><span class="lineno"> 22</span> <span class="keyword">namespace </span>faiss {</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="comment">/*******************************************************************</span></div>
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<div class="line"><a name="l00025"></a><span class="lineno"> 25</span> <span class="comment"> * ScalarQuantizer implementation</span></div>
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<div class="line"><a name="l00026"></a><span class="lineno"> 26</span> <span class="comment"> *</span></div>
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<div class="line"><a name="l00027"></a><span class="lineno"> 27</span> <span class="comment"> * The main source of complexity is to support combinations of 4</span></div>
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<div class="line"><a name="l00028"></a><span class="lineno"> 28</span> <span class="comment"> * variants without incurring runtime tests or virtual function calls:</span></div>
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<div class="line"><a name="l00029"></a><span class="lineno"> 29</span> <span class="comment"> *</span></div>
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<div class="line"><a name="l00030"></a><span class="lineno"> 30</span> <span class="comment"> * - 4 / 8 bits per code component</span></div>
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<div class="line"><a name="l00031"></a><span class="lineno"> 31</span> <span class="comment"> * - uniform / non-uniform</span></div>
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<div class="line"><a name="l00032"></a><span class="lineno"> 32</span> <span class="comment"> * - IP / L2 distance search</span></div>
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<div class="line"><a name="l00033"></a><span class="lineno"> 33</span> <span class="comment"> * - scalar / AVX distance computation</span></div>
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<div class="line"><a name="l00034"></a><span class="lineno"> 34</span> <span class="comment"> *</span></div>
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<div class="line"><a name="l00035"></a><span class="lineno"> 35</span> <span class="comment"> * The appropriate Quantizer object is returned via select_quantizer</span></div>
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<div class="line"><a name="l00036"></a><span class="lineno"> 36</span> <span class="comment"> * that hides the template mess.</span></div>
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<div class="line"><a name="l00037"></a><span class="lineno"> 37</span> <span class="comment"> ********************************************************************/</span></div>
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<div class="line"><a name="l00038"></a><span class="lineno"> 38</span> </div>
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<div class="line"><a name="l00039"></a><span class="lineno"> 39</span> <span class="preprocessor">#ifdef __AVX__</span></div>
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<div class="line"><a name="l00040"></a><span class="lineno"> 40</span> <span class="preprocessor"></span><span class="preprocessor">#define USE_AVX</span></div>
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<div class="line"><a name="l00041"></a><span class="lineno"> 41</span> <span class="preprocessor"></span><span class="preprocessor">#endif</span></div>
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<div class="line"><a name="l00042"></a><span class="lineno"> 42</span> <span class="preprocessor"></span></div>
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<div class="line"><a name="l00043"></a><span class="lineno"> 43</span> </div>
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<div class="line"><a name="l00044"></a><span class="lineno"> 44</span> <span class="keyword">namespace </span>{</div>
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<div class="line"><a name="l00045"></a><span class="lineno"> 45</span> </div>
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<div class="line"><a name="l00046"></a><span class="lineno"> 46</span> <span class="keyword">typedef</span> <a class="code" href="structfaiss_1_1Index.html#a040c6aed1f224f3ea7bf58eebc0c31a4">Index::idx_t</a> idx_t;</div>
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<div class="line"><a name="l00047"></a><span class="lineno"> 47</span> <span class="keyword">typedef</span> <a class="code" href="structfaiss_1_1ScalarQuantizer.html#a1201dbd1611fa5c10782ade5d0e4952e">ScalarQuantizer::QuantizerType</a> QuantizerType;</div>
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<div class="line"><a name="l00048"></a><span class="lineno"> 48</span> <span class="keyword">typedef</span> <a class="code" href="structfaiss_1_1ScalarQuantizer.html#a867ad0000e4ccfd40bbb1e01e7882d06">ScalarQuantizer::RangeStat</a> RangeStat;</div>
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<div class="line"><a name="l00049"></a><span class="lineno"> 49</span> </div>
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<div class="line"><a name="l00050"></a><span class="lineno"> 50</span> </div>
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<div class="line"><a name="l00051"></a><span class="lineno"> 51</span> <span class="comment">/*******************************************************************</span></div>
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<div class="line"><a name="l00052"></a><span class="lineno"> 52</span> <span class="comment"> * Codec: converts between values in [0, 1] and an index in a code</span></div>
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<div class="line"><a name="l00053"></a><span class="lineno"> 53</span> <span class="comment"> * array. The "i" parameter is the vector component index (not byte</span></div>
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<div class="line"><a name="l00054"></a><span class="lineno"> 54</span> <span class="comment"> * index).</span></div>
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<div class="line"><a name="l00055"></a><span class="lineno"> 55</span> <span class="comment"> */</span></div>
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<div class="line"><a name="l00056"></a><span class="lineno"> 56</span> </div>
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<div class="line"><a name="l00057"></a><span class="lineno"> 57</span> <span class="keyword">struct </span>Codec8bit {</div>
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<div class="line"><a name="l00058"></a><span class="lineno"> 58</span> </div>
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<div class="line"><a name="l00059"></a><span class="lineno"> 59</span>  <span class="keyword">static</span> <span class="keywordtype">void</span> encode_component (<span class="keywordtype">float</span> x, uint8_t *code, <span class="keywordtype">int</span> i) {</div>
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<div class="line"><a name="l00060"></a><span class="lineno"> 60</span>  code[i] = (int)(255 * x);</div>
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<div class="line"><a name="l00061"></a><span class="lineno"> 61</span>  }</div>
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<div class="line"><a name="l00062"></a><span class="lineno"> 62</span> </div>
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<div class="line"><a name="l00063"></a><span class="lineno"> 63</span>  <span class="keyword">static</span> <span class="keywordtype">float</span> decode_component (<span class="keyword">const</span> uint8_t *code, <span class="keywordtype">int</span> i) {</div>
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<div class="line"><a name="l00064"></a><span class="lineno"> 64</span>  <span class="keywordflow">return</span> (code[i] + 0.5f) / 255.0f;</div>
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<div class="line"><a name="l00065"></a><span class="lineno"> 65</span>  }</div>
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<div class="line"><a name="l00066"></a><span class="lineno"> 66</span> </div>
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<div class="line"><a name="l00067"></a><span class="lineno"> 67</span> <span class="preprocessor">#ifdef USE_AVX</span></div>
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<div class="line"><a name="l00068"></a><span class="lineno"> 68</span> <span class="preprocessor"></span> <span class="keyword">static</span> __m256 decode_8_components (<span class="keyword">const</span> uint8_t *code, <span class="keywordtype">int</span> i) {</div>
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<div class="line"><a name="l00069"></a><span class="lineno"> 69</span>  uint64_t c8 = *(uint64_t*)(code + i);</div>
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<div class="line"><a name="l00070"></a><span class="lineno"> 70</span>  __m128i c4lo = _mm_cvtepu8_epi32 (_mm_set1_epi32(c8));</div>
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<div class="line"><a name="l00071"></a><span class="lineno"> 71</span>  __m128i c4hi = _mm_cvtepu8_epi32 (_mm_set1_epi32(c8 >> 32));</div>
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<div class="line"><a name="l00072"></a><span class="lineno"> 72</span>  <span class="comment">// __m256i i8 = _mm256_set_m128i(c4lo, c4hi);</span></div>
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<div class="line"><a name="l00073"></a><span class="lineno"> 73</span>  __m256i i8 = _mm256_castsi128_si256 (c4lo);</div>
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<div class="line"><a name="l00074"></a><span class="lineno"> 74</span>  i8 = _mm256_insertf128_si256 (i8, c4hi, 1);</div>
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<div class="line"><a name="l00075"></a><span class="lineno"> 75</span>  __m256 f8 = _mm256_cvtepi32_ps (i8);</div>
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<div class="line"><a name="l00076"></a><span class="lineno"> 76</span>  __m256 half = _mm256_set1_ps (0.5f);</div>
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<div class="line"><a name="l00077"></a><span class="lineno"> 77</span>  f8 += half;</div>
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<div class="line"><a name="l00078"></a><span class="lineno"> 78</span>  __m256 one_255 = _mm256_set1_ps (1.f / 255.f);</div>
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<div class="line"><a name="l00079"></a><span class="lineno"> 79</span>  <span class="keywordflow">return</span> f8 * one_255;</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="preprocessor">#endif</span></div>
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<div class="line"><a name="l00082"></a><span class="lineno"> 82</span> <span class="preprocessor"></span>};</div>
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<div class="line"><a name="l00083"></a><span class="lineno"> 83</span> </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> <span class="keyword">struct </span>Codec4bit {</div>
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<div class="line"><a name="l00086"></a><span class="lineno"> 86</span> </div>
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<div class="line"><a name="l00087"></a><span class="lineno"> 87</span>  <span class="keyword">static</span> <span class="keywordtype">void</span> encode_component (<span class="keywordtype">float</span> x, uint8_t *code, <span class="keywordtype">int</span> i) {</div>
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<div class="line"><a name="l00088"></a><span class="lineno"> 88</span>  code [i / 2] |= (int)(x * 15.0) << ((i & 1) << 2);</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> </div>
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<div class="line"><a name="l00091"></a><span class="lineno"> 91</span>  <span class="keyword">static</span> <span class="keywordtype">float</span> decode_component (<span class="keyword">const</span> uint8_t *code, <span class="keywordtype">int</span> i) {</div>
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<div class="line"><a name="l00092"></a><span class="lineno"> 92</span>  <span class="keywordflow">return</span> (((code[i / 2] >> ((i & 1) << 2)) & 0xf) + 0.5f) / 15.0f;</div>
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<div class="line"><a name="l00093"></a><span class="lineno"> 93</span>  }</div>
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<div class="line"><a name="l00094"></a><span class="lineno"> 94</span> </div>
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<div class="line"><a name="l00095"></a><span class="lineno"> 95</span> </div>
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<div class="line"><a name="l00096"></a><span class="lineno"> 96</span> <span class="preprocessor">#ifdef USE_AVX</span></div>
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<div class="line"><a name="l00097"></a><span class="lineno"> 97</span> <span class="preprocessor"></span> <span class="keyword">static</span> __m256 decode_8_components (<span class="keyword">const</span> uint8_t *code, <span class="keywordtype">int</span> i) {</div>
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<div class="line"><a name="l00098"></a><span class="lineno"> 98</span>  uint32_t c4 = *(uint32_t*)(code + (i >> 1));</div>
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<div class="line"><a name="l00099"></a><span class="lineno"> 99</span>  uint32_t mask = 0x0f0f0f0f;</div>
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<div class="line"><a name="l00100"></a><span class="lineno"> 100</span>  uint32_t c4ev = c4 & mask;</div>
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<div class="line"><a name="l00101"></a><span class="lineno"> 101</span>  uint32_t c4od = (c4 >> 4) & mask;</div>
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<div class="line"><a name="l00102"></a><span class="lineno"> 102</span> </div>
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<div class="line"><a name="l00103"></a><span class="lineno"> 103</span>  <span class="comment">// the 8 lower bytes of c8 contain the values</span></div>
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<div class="line"><a name="l00104"></a><span class="lineno"> 104</span>  __m128i c8 = _mm_unpacklo_epi8 (_mm_set1_epi32(c4ev),</div>
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<div class="line"><a name="l00105"></a><span class="lineno"> 105</span>  _mm_set1_epi32(c4od));</div>
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<div class="line"><a name="l00106"></a><span class="lineno"> 106</span>  __m128i c4lo = _mm_cvtepu8_epi32 (c8);</div>
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<div class="line"><a name="l00107"></a><span class="lineno"> 107</span>  __m128i c4hi = _mm_cvtepu8_epi32 (_mm_srli_si128(c8, 4));</div>
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<div class="line"><a name="l00108"></a><span class="lineno"> 108</span>  __m256i i8 = _mm256_castsi128_si256 (c4lo);</div>
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<div class="line"><a name="l00109"></a><span class="lineno"> 109</span>  i8 = _mm256_insertf128_si256 (i8, c4hi, 1);</div>
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<div class="line"><a name="l00110"></a><span class="lineno"> 110</span>  __m256 f8 = _mm256_cvtepi32_ps (i8);</div>
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<div class="line"><a name="l00111"></a><span class="lineno"> 111</span>  __m256 half = _mm256_set1_ps (0.5f);</div>
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<div class="line"><a name="l00112"></a><span class="lineno"> 112</span>  f8 += half;</div>
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<div class="line"><a name="l00113"></a><span class="lineno"> 113</span>  __m256 one_255 = _mm256_set1_ps (1.f / 15.f);</div>
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<div class="line"><a name="l00114"></a><span class="lineno"> 114</span>  <span class="keywordflow">return</span> f8 * one_255;</div>
|
|
<div class="line"><a name="l00115"></a><span class="lineno"> 115</span>  }</div>
|
|
<div class="line"><a name="l00116"></a><span class="lineno"> 116</span> <span class="preprocessor">#endif</span></div>
|
|
<div class="line"><a name="l00117"></a><span class="lineno"> 117</span> <span class="preprocessor"></span>};</div>
|
|
<div class="line"><a name="l00118"></a><span class="lineno"> 118</span> </div>
|
|
<div class="line"><a name="l00119"></a><span class="lineno"> 119</span> </div>
|
|
<div class="line"><a name="l00120"></a><span class="lineno"> 120</span> <span class="comment">/*******************************************************************</span></div>
|
|
<div class="line"><a name="l00121"></a><span class="lineno"> 121</span> <span class="comment"> * Similarity: gets vector components and computes a similarity wrt. a</span></div>
|
|
<div class="line"><a name="l00122"></a><span class="lineno"> 122</span> <span class="comment"> * query vector stored in the object</span></div>
|
|
<div class="line"><a name="l00123"></a><span class="lineno"> 123</span> <span class="comment"> */</span></div>
|
|
<div class="line"><a name="l00124"></a><span class="lineno"> 124</span> </div>
|
|
<div class="line"><a name="l00125"></a><span class="lineno"> 125</span> <span class="keyword">struct </span>SimilarityL2 {</div>
|
|
<div class="line"><a name="l00126"></a><span class="lineno"> 126</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> *y, *yi;</div>
|
|
<div class="line"><a name="l00127"></a><span class="lineno"> 127</span> </div>
|
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<div class="line"><a name="l00128"></a><span class="lineno"> 128</span>  <span class="keyword">explicit</span> SimilarityL2 (<span class="keyword">const</span> <span class="keywordtype">float</span> * y): y(y) {}</div>
|
|
<div class="line"><a name="l00129"></a><span class="lineno"> 129</span> </div>
|
|
<div class="line"><a name="l00130"></a><span class="lineno"> 130</span>  <span class="comment">/******* scalar accumulator *******/</span></div>
|
|
<div class="line"><a name="l00131"></a><span class="lineno"> 131</span> </div>
|
|
<div class="line"><a name="l00132"></a><span class="lineno"> 132</span>  <span class="keywordtype">float</span> accu;</div>
|
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<div class="line"><a name="l00133"></a><span class="lineno"> 133</span> </div>
|
|
<div class="line"><a name="l00134"></a><span class="lineno"> 134</span>  <span class="keywordtype">void</span> begin () {</div>
|
|
<div class="line"><a name="l00135"></a><span class="lineno"> 135</span>  accu = 0;</div>
|
|
<div class="line"><a name="l00136"></a><span class="lineno"> 136</span>  yi = y;</div>
|
|
<div class="line"><a name="l00137"></a><span class="lineno"> 137</span>  }</div>
|
|
<div class="line"><a name="l00138"></a><span class="lineno"> 138</span> </div>
|
|
<div class="line"><a name="l00139"></a><span class="lineno"> 139</span>  <span class="keywordtype">void</span> add_component (<span class="keywordtype">float</span> x) {</div>
|
|
<div class="line"><a name="l00140"></a><span class="lineno"> 140</span>  <span class="keywordtype">float</span> tmp = *yi++ - x;</div>
|
|
<div class="line"><a name="l00141"></a><span class="lineno"> 141</span>  accu += tmp * tmp;</div>
|
|
<div class="line"><a name="l00142"></a><span class="lineno"> 142</span>  }</div>
|
|
<div class="line"><a name="l00143"></a><span class="lineno"> 143</span> </div>
|
|
<div class="line"><a name="l00144"></a><span class="lineno"> 144</span>  <span class="keywordtype">float</span> result () {</div>
|
|
<div class="line"><a name="l00145"></a><span class="lineno"> 145</span>  <span class="keywordflow">return</span> accu;</div>
|
|
<div class="line"><a name="l00146"></a><span class="lineno"> 146</span>  }</div>
|
|
<div class="line"><a name="l00147"></a><span class="lineno"> 147</span> </div>
|
|
<div class="line"><a name="l00148"></a><span class="lineno"> 148</span> <span class="preprocessor">#ifdef USE_AVX</span></div>
|
|
<div class="line"><a name="l00149"></a><span class="lineno"> 149</span> <span class="preprocessor"></span> <span class="comment">/******* AVX accumulator *******/</span></div>
|
|
<div class="line"><a name="l00150"></a><span class="lineno"> 150</span> </div>
|
|
<div class="line"><a name="l00151"></a><span class="lineno"> 151</span>  __m256 accu8;</div>
|
|
<div class="line"><a name="l00152"></a><span class="lineno"> 152</span> </div>
|
|
<div class="line"><a name="l00153"></a><span class="lineno"> 153</span>  <span class="keywordtype">void</span> begin_8 () {</div>
|
|
<div class="line"><a name="l00154"></a><span class="lineno"> 154</span>  accu8 = _mm256_setzero_ps();</div>
|
|
<div class="line"><a name="l00155"></a><span class="lineno"> 155</span>  yi = y;</div>
|
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<div class="line"><a name="l00156"></a><span class="lineno"> 156</span>  }</div>
|
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<div class="line"><a name="l00157"></a><span class="lineno"> 157</span> </div>
|
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<div class="line"><a name="l00158"></a><span class="lineno"> 158</span>  <span class="keywordtype">void</span> add_8_components (__m256 x) {</div>
|
|
<div class="line"><a name="l00159"></a><span class="lineno"> 159</span>  __m256 yiv = _mm256_loadu_ps (yi);</div>
|
|
<div class="line"><a name="l00160"></a><span class="lineno"> 160</span>  yi += 8;</div>
|
|
<div class="line"><a name="l00161"></a><span class="lineno"> 161</span>  __m256 tmp = yiv - x;</div>
|
|
<div class="line"><a name="l00162"></a><span class="lineno"> 162</span>  accu8 += tmp * tmp;</div>
|
|
<div class="line"><a name="l00163"></a><span class="lineno"> 163</span>  }</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="keywordtype">float</span> result_8 () {</div>
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|
<div class="line"><a name="l00166"></a><span class="lineno"> 166</span>  __m256 sum = _mm256_hadd_ps(accu8, accu8);</div>
|
|
<div class="line"><a name="l00167"></a><span class="lineno"> 167</span>  __m256 sum2 = _mm256_hadd_ps(sum, sum);</div>
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|
<div class="line"><a name="l00168"></a><span class="lineno"> 168</span>  <span class="comment">// now add the 0th and 4th component</span></div>
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|
<div class="line"><a name="l00169"></a><span class="lineno"> 169</span>  <span class="keywordflow">return</span></div>
|
|
<div class="line"><a name="l00170"></a><span class="lineno"> 170</span>  _mm_cvtss_f32 (_mm256_castps256_ps128(sum2)) +</div>
|
|
<div class="line"><a name="l00171"></a><span class="lineno"> 171</span>  _mm_cvtss_f32 (_mm256_extractf128_ps(sum2, 1));</div>
|
|
<div class="line"><a name="l00172"></a><span class="lineno"> 172</span>  }</div>
|
|
<div class="line"><a name="l00173"></a><span class="lineno"> 173</span> <span class="preprocessor">#endif</span></div>
|
|
<div class="line"><a name="l00174"></a><span class="lineno"> 174</span> <span class="preprocessor"></span>};</div>
|
|
<div class="line"><a name="l00175"></a><span class="lineno"> 175</span> </div>
|
|
<div class="line"><a name="l00176"></a><span class="lineno"> 176</span> <span class="keyword">struct </span>SimilarityIP {</div>
|
|
<div class="line"><a name="l00177"></a><span class="lineno"> 177</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> *y, *yi;</div>
|
|
<div class="line"><a name="l00178"></a><span class="lineno"> 178</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> accu0;</div>
|
|
<div class="line"><a name="l00179"></a><span class="lineno"> 179</span> </div>
|
|
<div class="line"><a name="l00180"></a><span class="lineno"> 180</span>  <span class="comment">/******* scalar accumulator *******/</span></div>
|
|
<div class="line"><a name="l00181"></a><span class="lineno"> 181</span> </div>
|
|
<div class="line"><a name="l00182"></a><span class="lineno"> 182</span>  <span class="keywordtype">float</span> accu;</div>
|
|
<div class="line"><a name="l00183"></a><span class="lineno"> 183</span> </div>
|
|
<div class="line"><a name="l00184"></a><span class="lineno"> 184</span>  SimilarityIP (<span class="keyword">const</span> <span class="keywordtype">float</span> * y, <span class="keywordtype">float</span> accu0):</div>
|
|
<div class="line"><a name="l00185"></a><span class="lineno"> 185</span>  y (y), accu0 (accu0) {}</div>
|
|
<div class="line"><a name="l00186"></a><span class="lineno"> 186</span> </div>
|
|
<div class="line"><a name="l00187"></a><span class="lineno"> 187</span>  <span class="keywordtype">void</span> begin () {</div>
|
|
<div class="line"><a name="l00188"></a><span class="lineno"> 188</span>  accu = accu0;</div>
|
|
<div class="line"><a name="l00189"></a><span class="lineno"> 189</span>  yi = y;</div>
|
|
<div class="line"><a name="l00190"></a><span class="lineno"> 190</span>  }</div>
|
|
<div class="line"><a name="l00191"></a><span class="lineno"> 191</span> </div>
|
|
<div class="line"><a name="l00192"></a><span class="lineno"> 192</span>  <span class="keywordtype">void</span> add_component (<span class="keywordtype">float</span> x) {</div>
|
|
<div class="line"><a name="l00193"></a><span class="lineno"> 193</span>  accu += *yi++ * x;</div>
|
|
<div class="line"><a name="l00194"></a><span class="lineno"> 194</span>  }</div>
|
|
<div class="line"><a name="l00195"></a><span class="lineno"> 195</span> </div>
|
|
<div class="line"><a name="l00196"></a><span class="lineno"> 196</span>  <span class="keywordtype">float</span> result () {</div>
|
|
<div class="line"><a name="l00197"></a><span class="lineno"> 197</span>  <span class="keywordflow">return</span> accu;</div>
|
|
<div class="line"><a name="l00198"></a><span class="lineno"> 198</span>  }</div>
|
|
<div class="line"><a name="l00199"></a><span class="lineno"> 199</span> </div>
|
|
<div class="line"><a name="l00200"></a><span class="lineno"> 200</span> <span class="preprocessor">#ifdef USE_AVX</span></div>
|
|
<div class="line"><a name="l00201"></a><span class="lineno"> 201</span> <span class="preprocessor"></span> <span class="comment">/******* AVX accumulator *******/</span></div>
|
|
<div class="line"><a name="l00202"></a><span class="lineno"> 202</span> </div>
|
|
<div class="line"><a name="l00203"></a><span class="lineno"> 203</span>  __m256 accu8;</div>
|
|
<div class="line"><a name="l00204"></a><span class="lineno"> 204</span> </div>
|
|
<div class="line"><a name="l00205"></a><span class="lineno"> 205</span>  <span class="keywordtype">void</span> begin_8 () {</div>
|
|
<div class="line"><a name="l00206"></a><span class="lineno"> 206</span>  accu8 = _mm256_setzero_ps();</div>
|
|
<div class="line"><a name="l00207"></a><span class="lineno"> 207</span>  yi = y;</div>
|
|
<div class="line"><a name="l00208"></a><span class="lineno"> 208</span>  }</div>
|
|
<div class="line"><a name="l00209"></a><span class="lineno"> 209</span> </div>
|
|
<div class="line"><a name="l00210"></a><span class="lineno"> 210</span>  <span class="keywordtype">void</span> add_8_components (__m256 x) {</div>
|
|
<div class="line"><a name="l00211"></a><span class="lineno"> 211</span>  __m256 yiv = _mm256_loadu_ps (yi);</div>
|
|
<div class="line"><a name="l00212"></a><span class="lineno"> 212</span>  yi += 8;</div>
|
|
<div class="line"><a name="l00213"></a><span class="lineno"> 213</span>  accu8 += yiv * x;</div>
|
|
<div class="line"><a name="l00214"></a><span class="lineno"> 214</span>  }</div>
|
|
<div class="line"><a name="l00215"></a><span class="lineno"> 215</span> </div>
|
|
<div class="line"><a name="l00216"></a><span class="lineno"> 216</span>  <span class="keywordtype">float</span> result_8 () {</div>
|
|
<div class="line"><a name="l00217"></a><span class="lineno"> 217</span>  __m256 sum = _mm256_hadd_ps(accu8, accu8);</div>
|
|
<div class="line"><a name="l00218"></a><span class="lineno"> 218</span>  __m256 sum2 = _mm256_hadd_ps(sum, sum);</div>
|
|
<div class="line"><a name="l00219"></a><span class="lineno"> 219</span>  <span class="comment">// now add the 0th and 4th component</span></div>
|
|
<div class="line"><a name="l00220"></a><span class="lineno"> 220</span>  <span class="keywordflow">return</span></div>
|
|
<div class="line"><a name="l00221"></a><span class="lineno"> 221</span>  accu0 +</div>
|
|
<div class="line"><a name="l00222"></a><span class="lineno"> 222</span>  _mm_cvtss_f32 (_mm256_castps256_ps128(sum2)) +</div>
|
|
<div class="line"><a name="l00223"></a><span class="lineno"> 223</span>  _mm_cvtss_f32 (_mm256_extractf128_ps(sum2, 1));</div>
|
|
<div class="line"><a name="l00224"></a><span class="lineno"> 224</span>  }</div>
|
|
<div class="line"><a name="l00225"></a><span class="lineno"> 225</span> <span class="preprocessor">#endif</span></div>
|
|
<div class="line"><a name="l00226"></a><span class="lineno"> 226</span> <span class="preprocessor"></span>};</div>
|
|
<div class="line"><a name="l00227"></a><span class="lineno"> 227</span> </div>
|
|
<div class="line"><a name="l00228"></a><span class="lineno"> 228</span> </div>
|
|
<div class="line"><a name="l00229"></a><span class="lineno"> 229</span> <span class="comment">/*******************************************************************</span></div>
|
|
<div class="line"><a name="l00230"></a><span class="lineno"> 230</span> <span class="comment"> * templatized distance functions</span></div>
|
|
<div class="line"><a name="l00231"></a><span class="lineno"> 231</span> <span class="comment"> */</span></div>
|
|
<div class="line"><a name="l00232"></a><span class="lineno"> 232</span> </div>
|
|
<div class="line"><a name="l00233"></a><span class="lineno"> 233</span> </div>
|
|
<div class="line"><a name="l00234"></a><span class="lineno"> 234</span> <span class="keyword">template</span><<span class="keyword">class</span> Quantizer, <span class="keyword">class</span> Similarity></div>
|
|
<div class="line"><a name="l00235"></a><span class="lineno"> 235</span> <span class="keywordtype">float</span> compute_distance(<span class="keyword">const</span> Quantizer & quant, Similarity & sim,</div>
|
|
<div class="line"><a name="l00236"></a><span class="lineno"> 236</span>  <span class="keyword">const</span> uint8_t *code)</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>  sim.begin();</div>
|
|
<div class="line"><a name="l00239"></a><span class="lineno"> 239</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < quant.d; i++) {</div>
|
|
<div class="line"><a name="l00240"></a><span class="lineno"> 240</span>  <span class="keywordtype">float</span> xi = quant.reconstruct_component (code, i);</div>
|
|
<div class="line"><a name="l00241"></a><span class="lineno"> 241</span>  sim.add_component (xi);</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="keywordflow">return</span> sim.result();</div>
|
|
<div class="line"><a name="l00244"></a><span class="lineno"> 244</span> }</div>
|
|
<div class="line"><a name="l00245"></a><span class="lineno"> 245</span> </div>
|
|
<div class="line"><a name="l00246"></a><span class="lineno"> 246</span> <span class="preprocessor">#ifdef USE_AVX</span></div>
|
|
<div class="line"><a name="l00247"></a><span class="lineno"> 247</span> <span class="preprocessor"></span><span class="keyword">template</span><<span class="keyword">class</span> Quantizer, <span class="keyword">class</span> Similarity></div>
|
|
<div class="line"><a name="l00248"></a><span class="lineno"> 248</span> <span class="keywordtype">float</span> compute_distance_8(<span class="keyword">const</span> Quantizer & quant, Similarity & sim,</div>
|
|
<div class="line"><a name="l00249"></a><span class="lineno"> 249</span>  <span class="keyword">const</span> uint8_t *code)</div>
|
|
<div class="line"><a name="l00250"></a><span class="lineno"> 250</span> {</div>
|
|
<div class="line"><a name="l00251"></a><span class="lineno"> 251</span>  sim.begin_8();</div>
|
|
<div class="line"><a name="l00252"></a><span class="lineno"> 252</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < quant.d; i += 8) {</div>
|
|
<div class="line"><a name="l00253"></a><span class="lineno"> 253</span>  __m256 xi = quant.reconstruct_8_components (code, i);</div>
|
|
<div class="line"><a name="l00254"></a><span class="lineno"> 254</span>  sim.add_8_components (xi);</div>
|
|
<div class="line"><a name="l00255"></a><span class="lineno"> 255</span>  }</div>
|
|
<div class="line"><a name="l00256"></a><span class="lineno"> 256</span>  <span class="keywordflow">return</span> sim.result_8();</div>
|
|
<div class="line"><a name="l00257"></a><span class="lineno"> 257</span> }</div>
|
|
<div class="line"><a name="l00258"></a><span class="lineno"> 258</span> <span class="preprocessor">#endif</span></div>
|
|
<div class="line"><a name="l00259"></a><span class="lineno"> 259</span> <span class="preprocessor"></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> <span class="comment">/*******************************************************************</span></div>
|
|
<div class="line"><a name="l00262"></a><span class="lineno"> 262</span> <span class="comment"> * Quantizer range training</span></div>
|
|
<div class="line"><a name="l00263"></a><span class="lineno"> 263</span> <span class="comment"> */</span></div>
|
|
<div class="line"><a name="l00264"></a><span class="lineno"> 264</span> </div>
|
|
<div class="line"><a name="l00265"></a><span class="lineno"> 265</span> <span class="keyword">static</span> <span class="keywordtype">float</span> sqr (<span class="keywordtype">float</span> x) {</div>
|
|
<div class="line"><a name="l00266"></a><span class="lineno"> 266</span>  <span class="keywordflow">return</span> x * x;</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> </div>
|
|
<div class="line"><a name="l00269"></a><span class="lineno"> 269</span> </div>
|
|
<div class="line"><a name="l00270"></a><span class="lineno"> 270</span> <span class="keywordtype">void</span> train_Uniform(RangeStat rs, <span class="keywordtype">float</span> rs_arg,</div>
|
|
<div class="line"><a name="l00271"></a><span class="lineno"> 271</span>  idx_t n, <span class="keywordtype">int</span> k, <span class="keyword">const</span> <span class="keywordtype">float</span> *x,</div>
|
|
<div class="line"><a name="l00272"></a><span class="lineno"> 272</span>  std::vector<float> & trained)</div>
|
|
<div class="line"><a name="l00273"></a><span class="lineno"> 273</span> {</div>
|
|
<div class="line"><a name="l00274"></a><span class="lineno"> 274</span>  trained.resize (2);</div>
|
|
<div class="line"><a name="l00275"></a><span class="lineno"> 275</span>  <span class="keywordtype">float</span> & vmin = trained[0];</div>
|
|
<div class="line"><a name="l00276"></a><span class="lineno"> 276</span>  <span class="keywordtype">float</span> & vmax = trained[1];</div>
|
|
<div class="line"><a name="l00277"></a><span class="lineno"> 277</span> </div>
|
|
<div class="line"><a name="l00278"></a><span class="lineno"> 278</span>  <span class="keywordflow">if</span> (rs == <a class="code" href="structfaiss_1_1ScalarQuantizer.html#a867ad0000e4ccfd40bbb1e01e7882d06aa52f2f14616c61c04baf6323d43588fd">ScalarQuantizer::RS_minmax</a>) {</div>
|
|
<div class="line"><a name="l00279"></a><span class="lineno"> 279</span>  vmin = HUGE_VAL; vmax = -HUGE_VAL;</div>
|
|
<div class="line"><a name="l00280"></a><span class="lineno"> 280</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < n; i++) {</div>
|
|
<div class="line"><a name="l00281"></a><span class="lineno"> 281</span>  <span class="keywordflow">if</span> (x[i] < vmin) vmin = x[i];</div>
|
|
<div class="line"><a name="l00282"></a><span class="lineno"> 282</span>  <span class="keywordflow">if</span> (x[i] > vmax) vmax = x[i];</div>
|
|
<div class="line"><a name="l00283"></a><span class="lineno"> 283</span>  }</div>
|
|
<div class="line"><a name="l00284"></a><span class="lineno"> 284</span>  <span class="keywordtype">float</span> vexp = (vmax - vmin) * rs_arg;</div>
|
|
<div class="line"><a name="l00285"></a><span class="lineno"> 285</span>  vmin -= vexp;</div>
|
|
<div class="line"><a name="l00286"></a><span class="lineno"> 286</span>  vmax += vexp;</div>
|
|
<div class="line"><a name="l00287"></a><span class="lineno"> 287</span>  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (rs == <a class="code" href="structfaiss_1_1ScalarQuantizer.html#a867ad0000e4ccfd40bbb1e01e7882d06afb4b9f4ee9003fa0193e6de69632f7a0">ScalarQuantizer::RS_meanstd</a>) {</div>
|
|
<div class="line"><a name="l00288"></a><span class="lineno"> 288</span>  <span class="keywordtype">double</span> sum = 0, sum2 = 0;</div>
|
|
<div class="line"><a name="l00289"></a><span class="lineno"> 289</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < n; i++) {</div>
|
|
<div class="line"><a name="l00290"></a><span class="lineno"> 290</span>  sum += x[i];</div>
|
|
<div class="line"><a name="l00291"></a><span class="lineno"> 291</span>  sum2 += x[i] * x[i];</div>
|
|
<div class="line"><a name="l00292"></a><span class="lineno"> 292</span>  }</div>
|
|
<div class="line"><a name="l00293"></a><span class="lineno"> 293</span>  <span class="keywordtype">float</span> mean = sum / n;</div>
|
|
<div class="line"><a name="l00294"></a><span class="lineno"> 294</span>  <span class="keywordtype">float</span> var = sum2 / n - mean * mean;</div>
|
|
<div class="line"><a name="l00295"></a><span class="lineno"> 295</span>  <span class="keywordtype">float</span> std = var <= 0 ? 1.0 : sqrt(var);</div>
|
|
<div class="line"><a name="l00296"></a><span class="lineno"> 296</span> </div>
|
|
<div class="line"><a name="l00297"></a><span class="lineno"> 297</span>  vmin = mean - std * rs_arg ;</div>
|
|
<div class="line"><a name="l00298"></a><span class="lineno"> 298</span>  vmax = mean + std * rs_arg ;</div>
|
|
<div class="line"><a name="l00299"></a><span class="lineno"> 299</span>  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (rs == <a class="code" href="structfaiss_1_1ScalarQuantizer.html#a867ad0000e4ccfd40bbb1e01e7882d06ae41cccec3a7acbcb3a47fa63c2bfb4c8">ScalarQuantizer::RS_quantiles</a>) {</div>
|
|
<div class="line"><a name="l00300"></a><span class="lineno"> 300</span>  std::vector<float> x_copy(n);</div>
|
|
<div class="line"><a name="l00301"></a><span class="lineno"> 301</span>  memcpy(x_copy.data(), x, n * <span class="keyword">sizeof</span>(*x));</div>
|
|
<div class="line"><a name="l00302"></a><span class="lineno"> 302</span>  <span class="comment">// TODO just do a qucikselect</span></div>
|
|
<div class="line"><a name="l00303"></a><span class="lineno"> 303</span>  std::sort(x_copy.begin(), x_copy.end());</div>
|
|
<div class="line"><a name="l00304"></a><span class="lineno"> 304</span>  <span class="keywordtype">int</span> o = int(rs_arg * n);</div>
|
|
<div class="line"><a name="l00305"></a><span class="lineno"> 305</span>  <span class="keywordflow">if</span> (o < 0) o = 0;</div>
|
|
<div class="line"><a name="l00306"></a><span class="lineno"> 306</span>  <span class="keywordflow">if</span> (o > n - o) o = n / 2;</div>
|
|
<div class="line"><a name="l00307"></a><span class="lineno"> 307</span>  vmin = x_copy[o];</div>
|
|
<div class="line"><a name="l00308"></a><span class="lineno"> 308</span>  vmax = x_copy[n - 1 - o];</div>
|
|
<div class="line"><a name="l00309"></a><span class="lineno"> 309</span> </div>
|
|
<div class="line"><a name="l00310"></a><span class="lineno"> 310</span>  } <span class="keywordflow">else</span> <span class="keywordflow">if</span> (rs == <a class="code" href="structfaiss_1_1ScalarQuantizer.html#a867ad0000e4ccfd40bbb1e01e7882d06ab0709ff74c1b882b64a7fdd7ca5df9a3">ScalarQuantizer::RS_optim</a>) {</div>
|
|
<div class="line"><a name="l00311"></a><span class="lineno"> 311</span>  <span class="keywordtype">float</span> a, b;</div>
|
|
<div class="line"><a name="l00312"></a><span class="lineno"> 312</span>  <span class="keywordtype">float</span> sx = 0;</div>
|
|
<div class="line"><a name="l00313"></a><span class="lineno"> 313</span>  {</div>
|
|
<div class="line"><a name="l00314"></a><span class="lineno"> 314</span>  vmin = HUGE_VAL, vmax = -HUGE_VAL;</div>
|
|
<div class="line"><a name="l00315"></a><span class="lineno"> 315</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < n; i++) {</div>
|
|
<div class="line"><a name="l00316"></a><span class="lineno"> 316</span>  <span class="keywordflow">if</span> (x[i] < vmin) vmin = x[i];</div>
|
|
<div class="line"><a name="l00317"></a><span class="lineno"> 317</span>  <span class="keywordflow">if</span> (x[i] > vmax) vmax = x[i];</div>
|
|
<div class="line"><a name="l00318"></a><span class="lineno"> 318</span>  sx += x[i];</div>
|
|
<div class="line"><a name="l00319"></a><span class="lineno"> 319</span>  }</div>
|
|
<div class="line"><a name="l00320"></a><span class="lineno"> 320</span>  b = vmin;</div>
|
|
<div class="line"><a name="l00321"></a><span class="lineno"> 321</span>  a = (vmax - vmin) / (k - 1);</div>
|
|
<div class="line"><a name="l00322"></a><span class="lineno"> 322</span>  }</div>
|
|
<div class="line"><a name="l00323"></a><span class="lineno"> 323</span>  <span class="keywordtype">int</span> verbose = <span class="keyword">false</span>;</div>
|
|
<div class="line"><a name="l00324"></a><span class="lineno"> 324</span>  <span class="keywordtype">int</span> niter = 2000;</div>
|
|
<div class="line"><a name="l00325"></a><span class="lineno"> 325</span>  <span class="keywordtype">float</span> last_err = -1;</div>
|
|
<div class="line"><a name="l00326"></a><span class="lineno"> 326</span>  <span class="keywordtype">int</span> iter_last_err = 0;</div>
|
|
<div class="line"><a name="l00327"></a><span class="lineno"> 327</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> it = 0; it < niter; it++) {</div>
|
|
<div class="line"><a name="l00328"></a><span class="lineno"> 328</span>  <span class="keywordtype">float</span> sn = 0, sn2 = 0, sxn = 0, err1 = 0;</div>
|
|
<div class="line"><a name="l00329"></a><span class="lineno"> 329</span> </div>
|
|
<div class="line"><a name="l00330"></a><span class="lineno"> 330</span>  <span class="keywordflow">for</span> (idx_t i = 0; i < n; i++) {</div>
|
|
<div class="line"><a name="l00331"></a><span class="lineno"> 331</span>  <span class="keywordtype">float</span> xi = x[i];</div>
|
|
<div class="line"><a name="l00332"></a><span class="lineno"> 332</span>  <span class="keywordtype">float</span> ni = floor ((xi - b) / a + 0.5);</div>
|
|
<div class="line"><a name="l00333"></a><span class="lineno"> 333</span>  <span class="keywordflow">if</span> (ni < 0) ni = 0;</div>
|
|
<div class="line"><a name="l00334"></a><span class="lineno"> 334</span>  <span class="keywordflow">if</span> (ni >= k) ni = k - 1;</div>
|
|
<div class="line"><a name="l00335"></a><span class="lineno"> 335</span>  err1 += sqr (xi - (ni * a + b));</div>
|
|
<div class="line"><a name="l00336"></a><span class="lineno"> 336</span>  sn += ni;</div>
|
|
<div class="line"><a name="l00337"></a><span class="lineno"> 337</span>  sn2 += ni * ni;</div>
|
|
<div class="line"><a name="l00338"></a><span class="lineno"> 338</span>  sxn += ni * xi;</div>
|
|
<div class="line"><a name="l00339"></a><span class="lineno"> 339</span>  }</div>
|
|
<div class="line"><a name="l00340"></a><span class="lineno"> 340</span> </div>
|
|
<div class="line"><a name="l00341"></a><span class="lineno"> 341</span>  <span class="keywordflow">if</span> (err1 == last_err) {</div>
|
|
<div class="line"><a name="l00342"></a><span class="lineno"> 342</span>  iter_last_err ++;</div>
|
|
<div class="line"><a name="l00343"></a><span class="lineno"> 343</span>  <span class="keywordflow">if</span> (iter_last_err == 16) <span class="keywordflow">break</span>;</div>
|
|
<div class="line"><a name="l00344"></a><span class="lineno"> 344</span>  } <span class="keywordflow">else</span> {</div>
|
|
<div class="line"><a name="l00345"></a><span class="lineno"> 345</span>  last_err = err1;</div>
|
|
<div class="line"><a name="l00346"></a><span class="lineno"> 346</span>  iter_last_err = 0;</div>
|
|
<div class="line"><a name="l00347"></a><span class="lineno"> 347</span>  }</div>
|
|
<div class="line"><a name="l00348"></a><span class="lineno"> 348</span> </div>
|
|
<div class="line"><a name="l00349"></a><span class="lineno"> 349</span>  <span class="keywordtype">float</span> det = sqr (sn) - sn2 * n;</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>  b = (sn * sxn - sn2 * sx) / det;</div>
|
|
<div class="line"><a name="l00352"></a><span class="lineno"> 352</span>  a = (sn * sx - n * sxn) / det;</div>
|
|
<div class="line"><a name="l00353"></a><span class="lineno"> 353</span>  <span class="keywordflow">if</span> (verbose) {</div>
|
|
<div class="line"><a name="l00354"></a><span class="lineno"> 354</span>  printf (<span class="stringliteral">"it %d, err1=%g \r"</span>, it, err1);</div>
|
|
<div class="line"><a name="l00355"></a><span class="lineno"> 355</span>  fflush(stdout);</div>
|
|
<div class="line"><a name="l00356"></a><span class="lineno"> 356</span>  }</div>
|
|
<div class="line"><a name="l00357"></a><span class="lineno"> 357</span>  }</div>
|
|
<div class="line"><a name="l00358"></a><span class="lineno"> 358</span>  <span class="keywordflow">if</span> (verbose) printf(<span class="stringliteral">"\n"</span>);</div>
|
|
<div class="line"><a name="l00359"></a><span class="lineno"> 359</span> </div>
|
|
<div class="line"><a name="l00360"></a><span class="lineno"> 360</span>  vmin = b;</div>
|
|
<div class="line"><a name="l00361"></a><span class="lineno"> 361</span>  vmax = b + a * (k - 1);</div>
|
|
<div class="line"><a name="l00362"></a><span class="lineno"> 362</span> </div>
|
|
<div class="line"><a name="l00363"></a><span class="lineno"> 363</span>  } <span class="keywordflow">else</span> {</div>
|
|
<div class="line"><a name="l00364"></a><span class="lineno"> 364</span>  FAISS_THROW_MSG (<span class="stringliteral">"Invalid qtype"</span>);</div>
|
|
<div class="line"><a name="l00365"></a><span class="lineno"> 365</span>  }</div>
|
|
<div class="line"><a name="l00366"></a><span class="lineno"> 366</span>  vmax -= vmin;</div>
|
|
<div class="line"><a name="l00367"></a><span class="lineno"> 367</span> }</div>
|
|
<div class="line"><a name="l00368"></a><span class="lineno"> 368</span> </div>
|
|
<div class="line"><a name="l00369"></a><span class="lineno"> 369</span> <span class="keywordtype">void</span> train_NonUniform(RangeStat rs, <span class="keywordtype">float</span> rs_arg,</div>
|
|
<div class="line"><a name="l00370"></a><span class="lineno"> 370</span>  idx_t n, <span class="keywordtype">int</span> d, <span class="keywordtype">int</span> k, <span class="keyword">const</span> <span class="keywordtype">float</span> *x,</div>
|
|
<div class="line"><a name="l00371"></a><span class="lineno"> 371</span>  std::vector<float> & trained)</div>
|
|
<div class="line"><a name="l00372"></a><span class="lineno"> 372</span> {</div>
|
|
<div class="line"><a name="l00373"></a><span class="lineno"> 373</span>  trained.resize (2 * d);</div>
|
|
<div class="line"><a name="l00374"></a><span class="lineno"> 374</span>  <span class="keywordtype">float</span> * vmin = trained.data();</div>
|
|
<div class="line"><a name="l00375"></a><span class="lineno"> 375</span>  <span class="keywordtype">float</span> * vmax = trained.data() + d;</div>
|
|
<div class="line"><a name="l00376"></a><span class="lineno"> 376</span>  <span class="keywordflow">if</span> (rs == <a class="code" href="structfaiss_1_1ScalarQuantizer.html#a867ad0000e4ccfd40bbb1e01e7882d06aa52f2f14616c61c04baf6323d43588fd">ScalarQuantizer::RS_minmax</a>) {</div>
|
|
<div class="line"><a name="l00377"></a><span class="lineno"> 377</span>  memcpy (vmin, x, <span class="keyword">sizeof</span>(*x) * d);</div>
|
|
<div class="line"><a name="l00378"></a><span class="lineno"> 378</span>  memcpy (vmax, x, <span class="keyword">sizeof</span>(*x) * d);</div>
|
|
<div class="line"><a name="l00379"></a><span class="lineno"> 379</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 1; i < n; i++) {</div>
|
|
<div class="line"><a name="l00380"></a><span class="lineno"> 380</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> *xi = x + i * d;</div>
|
|
<div class="line"><a name="l00381"></a><span class="lineno"> 381</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> j = 0; j < d; j++) {</div>
|
|
<div class="line"><a name="l00382"></a><span class="lineno"> 382</span>  <span class="keywordflow">if</span> (xi[j] < vmin[j]) vmin[j] = xi[j];</div>
|
|
<div class="line"><a name="l00383"></a><span class="lineno"> 383</span>  <span class="keywordflow">if</span> (xi[j] > vmax[j]) vmax[j] = xi[j];</div>
|
|
<div class="line"><a name="l00384"></a><span class="lineno"> 384</span>  }</div>
|
|
<div class="line"><a name="l00385"></a><span class="lineno"> 385</span>  }</div>
|
|
<div class="line"><a name="l00386"></a><span class="lineno"> 386</span>  <span class="keywordtype">float</span> *vdiff = vmax;</div>
|
|
<div class="line"><a name="l00387"></a><span class="lineno"> 387</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> j = 0; j < d; j++) {</div>
|
|
<div class="line"><a name="l00388"></a><span class="lineno"> 388</span>  <span class="keywordtype">float</span> vexp = (vmax[j] - vmin[j]) * rs_arg;</div>
|
|
<div class="line"><a name="l00389"></a><span class="lineno"> 389</span>  vmin[j] -= vexp;</div>
|
|
<div class="line"><a name="l00390"></a><span class="lineno"> 390</span>  vmax[j] += vexp;</div>
|
|
<div class="line"><a name="l00391"></a><span class="lineno"> 391</span>  vdiff [j] = vmax[j] - vmin[j];</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="keywordflow">else</span> {</div>
|
|
<div class="line"><a name="l00394"></a><span class="lineno"> 394</span>  <span class="comment">// transpose</span></div>
|
|
<div class="line"><a name="l00395"></a><span class="lineno"> 395</span>  std::vector<float> xt(n * d);</div>
|
|
<div class="line"><a name="l00396"></a><span class="lineno"> 396</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 1; i < n; i++) {</div>
|
|
<div class="line"><a name="l00397"></a><span class="lineno"> 397</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> *xi = x + i * d;</div>
|
|
<div class="line"><a name="l00398"></a><span class="lineno"> 398</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> j = 0; j < d; j++) {</div>
|
|
<div class="line"><a name="l00399"></a><span class="lineno"> 399</span>  xt[j * n + i] = xi[j];</div>
|
|
<div class="line"><a name="l00400"></a><span class="lineno"> 400</span>  }</div>
|
|
<div class="line"><a name="l00401"></a><span class="lineno"> 401</span>  }</div>
|
|
<div class="line"><a name="l00402"></a><span class="lineno"> 402</span>  std::vector<float> trained_d(2);</div>
|
|
<div class="line"><a name="l00403"></a><span class="lineno"> 403</span> <span class="preprocessor">#pragma omp parallel for</span></div>
|
|
<div class="line"><a name="l00404"></a><span class="lineno"> 404</span> <span class="preprocessor"></span> <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> j = 0; j < d; j++) {</div>
|
|
<div class="line"><a name="l00405"></a><span class="lineno"> 405</span>  train_Uniform(rs, rs_arg,</div>
|
|
<div class="line"><a name="l00406"></a><span class="lineno"> 406</span>  n, k, xt.data() + j * n,</div>
|
|
<div class="line"><a name="l00407"></a><span class="lineno"> 407</span>  trained_d);</div>
|
|
<div class="line"><a name="l00408"></a><span class="lineno"> 408</span>  vmin[j] = trained_d[0];</div>
|
|
<div class="line"><a name="l00409"></a><span class="lineno"> 409</span>  vmax[j] = trained_d[1];</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>  }</div>
|
|
<div class="line"><a name="l00412"></a><span class="lineno"> 412</span> }</div>
|
|
<div class="line"><a name="l00413"></a><span class="lineno"> 413</span> </div>
|
|
<div class="line"><a name="l00414"></a><span class="lineno"> 414</span> </div>
|
|
<div class="line"><a name="l00415"></a><span class="lineno"> 415</span> <span class="comment">/*******************************************************************</span></div>
|
|
<div class="line"><a name="l00416"></a><span class="lineno"> 416</span> <span class="comment"> * Quantizer: normalizes scalar vector components, then passes them</span></div>
|
|
<div class="line"><a name="l00417"></a><span class="lineno"> 417</span> <span class="comment"> * through a codec</span></div>
|
|
<div class="line"><a name="l00418"></a><span class="lineno"> 418</span> <span class="comment"> */</span></div>
|
|
<div class="line"><a name="l00419"></a><span class="lineno"> 419</span> </div>
|
|
<div class="line"><a name="l00420"></a><span class="lineno"> 420</span> </div>
|
|
<div class="line"><a name="l00421"></a><span class="lineno"> 421</span> </div>
|
|
<div class="line"><a name="l00422"></a><span class="lineno"> 422</span> <span class="keyword">struct </span>Quantizer {</div>
|
|
<div class="line"><a name="l00423"></a><span class="lineno"> 423</span>  <span class="keyword">virtual</span> <span class="keywordtype">void</span> encode_vector(<span class="keyword">const</span> <span class="keywordtype">float</span> *x, uint8_t *code) <span class="keyword">const</span> = 0;</div>
|
|
<div class="line"><a name="l00424"></a><span class="lineno"> 424</span>  <span class="keyword">virtual</span> <span class="keywordtype">void</span> decode_vector(<span class="keyword">const</span> uint8_t *code, <span class="keywordtype">float</span> *x) <span class="keyword">const</span> = 0;</div>
|
|
<div class="line"><a name="l00425"></a><span class="lineno"> 425</span> </div>
|
|
<div class="line"><a name="l00426"></a><span class="lineno"> 426</span>  <span class="keyword">virtual</span> <span class="keywordtype">float</span> compute_distance_L2 (SimilarityL2 &sim,</div>
|
|
<div class="line"><a name="l00427"></a><span class="lineno"> 427</span>  <span class="keyword">const</span> uint8_t * codes) <span class="keyword">const</span> = 0;</div>
|
|
<div class="line"><a name="l00428"></a><span class="lineno"> 428</span>  <span class="keyword">virtual</span> <span class="keywordtype">float</span> compute_distance_IP (SimilarityIP &sim,</div>
|
|
<div class="line"><a name="l00429"></a><span class="lineno"> 429</span>  <span class="keyword">const</span> uint8_t * codes) <span class="keyword">const</span> = 0;</div>
|
|
<div class="line"><a name="l00430"></a><span class="lineno"> 430</span> </div>
|
|
<div class="line"><a name="l00431"></a><span class="lineno"> 431</span>  <span class="keyword">virtual</span> ~Quantizer() {}</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> </div>
|
|
<div class="line"><a name="l00434"></a><span class="lineno"> 434</span> </div>
|
|
<div class="line"><a name="l00435"></a><span class="lineno"> 435</span> </div>
|
|
<div class="line"><a name="l00436"></a><span class="lineno"> 436</span> </div>
|
|
<div class="line"><a name="l00437"></a><span class="lineno"> 437</span> <span class="keyword">template</span><<span class="keyword">class</span> Codec></div>
|
|
<div class="line"><a name="l00438"></a><span class="lineno"> 438</span> <span class="keyword">struct </span>QuantizerUniform: Quantizer {</div>
|
|
<div class="line"><a name="l00439"></a><span class="lineno"> 439</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> d;</div>
|
|
<div class="line"><a name="l00440"></a><span class="lineno"> 440</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> vmin, vdiff;</div>
|
|
<div class="line"><a name="l00441"></a><span class="lineno"> 441</span> </div>
|
|
<div class="line"><a name="l00442"></a><span class="lineno"> 442</span>  QuantizerUniform(<span class="keywordtype">size_t</span> d, <span class="keyword">const</span> std::vector<float> &trained):</div>
|
|
<div class="line"><a name="l00443"></a><span class="lineno"> 443</span>  d(d), vmin(trained[0]), vdiff(trained[1]) {</div>
|
|
<div class="line"><a name="l00444"></a><span class="lineno"> 444</span>  }</div>
|
|
<div class="line"><a name="l00445"></a><span class="lineno"> 445</span> </div>
|
|
<div class="line"><a name="l00446"></a><span class="lineno"> 446</span>  <span class="keywordtype">void</span> encode_vector(<span class="keyword">const</span> <span class="keywordtype">float</span>* x, uint8_t* code)<span class="keyword"> const override </span>{</div>
|
|
<div class="line"><a name="l00447"></a><span class="lineno"> 447</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < d; i++) {</div>
|
|
<div class="line"><a name="l00448"></a><span class="lineno"> 448</span>  <span class="keywordtype">float</span> xi = (x[i] - vmin) / vdiff;</div>
|
|
<div class="line"><a name="l00449"></a><span class="lineno"> 449</span>  <span class="keywordflow">if</span> (xi < 0)</div>
|
|
<div class="line"><a name="l00450"></a><span class="lineno"> 450</span>  xi = 0;</div>
|
|
<div class="line"><a name="l00451"></a><span class="lineno"> 451</span>  <span class="keywordflow">if</span> (xi > 1.0)</div>
|
|
<div class="line"><a name="l00452"></a><span class="lineno"> 452</span>  xi = 1.0;</div>
|
|
<div class="line"><a name="l00453"></a><span class="lineno"> 453</span>  Codec::encode_component(xi, code, i);</div>
|
|
<div class="line"><a name="l00454"></a><span class="lineno"> 454</span>  }</div>
|
|
<div class="line"><a name="l00455"></a><span class="lineno"> 455</span>  }</div>
|
|
<div class="line"><a name="l00456"></a><span class="lineno"> 456</span> </div>
|
|
<div class="line"><a name="l00457"></a><span class="lineno"> 457</span>  <span class="keywordtype">void</span> decode_vector(<span class="keyword">const</span> uint8_t* code, <span class="keywordtype">float</span>* x)<span class="keyword"> const override </span>{</div>
|
|
<div class="line"><a name="l00458"></a><span class="lineno"> 458</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < d; i++) {</div>
|
|
<div class="line"><a name="l00459"></a><span class="lineno"> 459</span>  <span class="keywordtype">float</span> xi = Codec::decode_component(code, i);</div>
|
|
<div class="line"><a name="l00460"></a><span class="lineno"> 460</span>  x[i] = vmin + xi * vdiff;</div>
|
|
<div class="line"><a name="l00461"></a><span class="lineno"> 461</span>  }</div>
|
|
<div class="line"><a name="l00462"></a><span class="lineno"> 462</span>  }</div>
|
|
<div class="line"><a name="l00463"></a><span class="lineno"> 463</span> </div>
|
|
<div class="line"><a name="l00464"></a><span class="lineno"> 464</span>  <span class="keywordtype">float</span> reconstruct_component (<span class="keyword">const</span> uint8_t * code, <span class="keywordtype">int</span> i)<span class="keyword"> const</span></div>
|
|
<div class="line"><a name="l00465"></a><span class="lineno"> 465</span> <span class="keyword"> </span>{</div>
|
|
<div class="line"><a name="l00466"></a><span class="lineno"> 466</span>  <span class="keywordtype">float</span> xi = Codec::decode_component (code, i);</div>
|
|
<div class="line"><a name="l00467"></a><span class="lineno"> 467</span>  <span class="keywordflow">return</span> vmin + xi * vdiff;</div>
|
|
<div class="line"><a name="l00468"></a><span class="lineno"> 468</span>  }</div>
|
|
<div class="line"><a name="l00469"></a><span class="lineno"> 469</span> </div>
|
|
<div class="line"><a name="l00470"></a><span class="lineno"> 470</span> <span class="preprocessor">#ifdef USE_AVX</span></div>
|
|
<div class="line"><a name="l00471"></a><span class="lineno"> 471</span> <span class="preprocessor"></span> __m256 reconstruct_8_components (<span class="keyword">const</span> uint8_t * code, <span class="keywordtype">int</span> i)<span class="keyword"> const</span></div>
|
|
<div class="line"><a name="l00472"></a><span class="lineno"> 472</span> <span class="keyword"> </span>{</div>
|
|
<div class="line"><a name="l00473"></a><span class="lineno"> 473</span>  __m256 xi = Codec::decode_8_components (code, i);</div>
|
|
<div class="line"><a name="l00474"></a><span class="lineno"> 474</span>  <span class="keywordflow">return</span> _mm256_set1_ps(vmin) + xi * _mm256_set1_ps (vdiff);</div>
|
|
<div class="line"><a name="l00475"></a><span class="lineno"> 475</span>  }</div>
|
|
<div class="line"><a name="l00476"></a><span class="lineno"> 476</span> <span class="preprocessor">#endif</span></div>
|
|
<div class="line"><a name="l00477"></a><span class="lineno"> 477</span> <span class="preprocessor"></span></div>
|
|
<div class="line"><a name="l00478"></a><span class="lineno"> 478</span>  <span class="keywordtype">float</span> compute_distance_L2(SimilarityL2& sim, <span class="keyword">const</span> uint8_t* codes)<span class="keyword"></span></div>
|
|
<div class="line"><a name="l00479"></a><span class="lineno"> 479</span> <span class="keyword"> const override </span>{</div>
|
|
<div class="line"><a name="l00480"></a><span class="lineno"> 480</span>  <span class="keywordflow">return</span> compute_distance(*<span class="keyword">this</span>, sim, codes);</div>
|
|
<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> </div>
|
|
<div class="line"><a name="l00483"></a><span class="lineno"> 483</span>  <span class="keywordtype">float</span> compute_distance_IP(SimilarityIP& sim, <span class="keyword">const</span> uint8_t* codes)<span class="keyword"></span></div>
|
|
<div class="line"><a name="l00484"></a><span class="lineno"> 484</span> <span class="keyword"> const override </span>{</div>
|
|
<div class="line"><a name="l00485"></a><span class="lineno"> 485</span>  <span class="keywordflow">return</span> compute_distance(*<span class="keyword">this</span>, sim, codes);</div>
|
|
<div class="line"><a name="l00486"></a><span class="lineno"> 486</span>  }</div>
|
|
<div class="line"><a name="l00487"></a><span class="lineno"> 487</span> };</div>
|
|
<div class="line"><a name="l00488"></a><span class="lineno"> 488</span> </div>
|
|
<div class="line"><a name="l00489"></a><span class="lineno"> 489</span> <span class="preprocessor">#ifdef USE_AVX</span></div>
|
|
<div class="line"><a name="l00490"></a><span class="lineno"> 490</span> <span class="preprocessor"></span><span class="keyword">template</span><<span class="keyword">class</span> Codec></div>
|
|
<div class="line"><a name="l00491"></a><span class="lineno"> 491</span> <span class="keyword">struct </span>QuantizerUniform8: QuantizerUniform<Codec> {</div>
|
|
<div class="line"><a name="l00492"></a><span class="lineno"> 492</span> </div>
|
|
<div class="line"><a name="l00493"></a><span class="lineno"> 493</span>  QuantizerUniform8 (<span class="keywordtype">size_t</span> d, <span class="keyword">const</span> std::vector<float> &trained):</div>
|
|
<div class="line"><a name="l00494"></a><span class="lineno"> 494</span>  QuantizerUniform<Codec> (d, trained) {}</div>
|
|
<div class="line"><a name="l00495"></a><span class="lineno"> 495</span> </div>
|
|
<div class="line"><a name="l00496"></a><span class="lineno"> 496</span>  <span class="keywordtype">float</span> compute_distance_L2(SimilarityL2& sim, <span class="keyword">const</span> uint8_t* codes)<span class="keyword"></span></div>
|
|
<div class="line"><a name="l00497"></a><span class="lineno"> 497</span> <span class="keyword"> const override </span>{</div>
|
|
<div class="line"><a name="l00498"></a><span class="lineno"> 498</span>  <span class="keywordflow">return</span> compute_distance_8(*<span class="keyword">this</span>, sim, codes);</div>
|
|
<div class="line"><a name="l00499"></a><span class="lineno"> 499</span>  }</div>
|
|
<div class="line"><a name="l00500"></a><span class="lineno"> 500</span> </div>
|
|
<div class="line"><a name="l00501"></a><span class="lineno"> 501</span>  <span class="keywordtype">float</span> compute_distance_IP(SimilarityIP& sim, <span class="keyword">const</span> uint8_t* codes)<span class="keyword"></span></div>
|
|
<div class="line"><a name="l00502"></a><span class="lineno"> 502</span> <span class="keyword"> const override </span>{</div>
|
|
<div class="line"><a name="l00503"></a><span class="lineno"> 503</span>  <span class="keywordflow">return</span> compute_distance_8(*<span class="keyword">this</span>, sim, codes);</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> <span class="preprocessor">#endif</span></div>
|
|
<div class="line"><a name="l00507"></a><span class="lineno"> 507</span> <span class="preprocessor"></span></div>
|
|
<div class="line"><a name="l00508"></a><span class="lineno"> 508</span> </div>
|
|
<div class="line"><a name="l00509"></a><span class="lineno"> 509</span> </div>
|
|
<div class="line"><a name="l00510"></a><span class="lineno"> 510</span> </div>
|
|
<div class="line"><a name="l00511"></a><span class="lineno"> 511</span> </div>
|
|
<div class="line"><a name="l00512"></a><span class="lineno"> 512</span> <span class="keyword">template</span><<span class="keyword">class</span> Codec></div>
|
|
<div class="line"><a name="l00513"></a><span class="lineno"> 513</span> <span class="keyword">struct </span>QuantizerNonUniform: Quantizer {</div>
|
|
<div class="line"><a name="l00514"></a><span class="lineno"> 514</span>  <span class="keyword">const</span> <span class="keywordtype">size_t</span> d;</div>
|
|
<div class="line"><a name="l00515"></a><span class="lineno"> 515</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> *vmin, *vdiff;</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>  QuantizerNonUniform(<span class="keywordtype">size_t</span> d, <span class="keyword">const</span> std::vector<float> &trained):</div>
|
|
<div class="line"><a name="l00518"></a><span class="lineno"> 518</span>  d(d), vmin(trained.data()), vdiff(trained.data() + d) {}</div>
|
|
<div class="line"><a name="l00519"></a><span class="lineno"> 519</span> </div>
|
|
<div class="line"><a name="l00520"></a><span class="lineno"> 520</span>  <span class="keywordtype">void</span> encode_vector(<span class="keyword">const</span> <span class="keywordtype">float</span>* x, uint8_t* code)<span class="keyword"> const override </span>{</div>
|
|
<div class="line"><a name="l00521"></a><span class="lineno"> 521</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < d; i++) {</div>
|
|
<div class="line"><a name="l00522"></a><span class="lineno"> 522</span>  <span class="keywordtype">float</span> xi = (x[i] - vmin[i]) / vdiff[i];</div>
|
|
<div class="line"><a name="l00523"></a><span class="lineno"> 523</span>  <span class="keywordflow">if</span> (xi < 0)</div>
|
|
<div class="line"><a name="l00524"></a><span class="lineno"> 524</span>  xi = 0;</div>
|
|
<div class="line"><a name="l00525"></a><span class="lineno"> 525</span>  <span class="keywordflow">if</span> (xi > 1.0)</div>
|
|
<div class="line"><a name="l00526"></a><span class="lineno"> 526</span>  xi = 1.0;</div>
|
|
<div class="line"><a name="l00527"></a><span class="lineno"> 527</span>  Codec::encode_component(xi, code, i);</div>
|
|
<div class="line"><a name="l00528"></a><span class="lineno"> 528</span>  }</div>
|
|
<div class="line"><a name="l00529"></a><span class="lineno"> 529</span>  }</div>
|
|
<div class="line"><a name="l00530"></a><span class="lineno"> 530</span> </div>
|
|
<div class="line"><a name="l00531"></a><span class="lineno"> 531</span>  <span class="keywordtype">void</span> decode_vector(<span class="keyword">const</span> uint8_t* code, <span class="keywordtype">float</span>* x)<span class="keyword"> const override </span>{</div>
|
|
<div class="line"><a name="l00532"></a><span class="lineno"> 532</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < d; i++) {</div>
|
|
<div class="line"><a name="l00533"></a><span class="lineno"> 533</span>  <span class="keywordtype">float</span> xi = Codec::decode_component(code, i);</div>
|
|
<div class="line"><a name="l00534"></a><span class="lineno"> 534</span>  x[i] = vmin[i] + xi * vdiff[i];</div>
|
|
<div class="line"><a name="l00535"></a><span class="lineno"> 535</span>  }</div>
|
|
<div class="line"><a name="l00536"></a><span class="lineno"> 536</span>  }</div>
|
|
<div class="line"><a name="l00537"></a><span class="lineno"> 537</span> </div>
|
|
<div class="line"><a name="l00538"></a><span class="lineno"> 538</span>  <span class="keywordtype">float</span> reconstruct_component (<span class="keyword">const</span> uint8_t * code, <span class="keywordtype">int</span> i)<span class="keyword"> const</span></div>
|
|
<div class="line"><a name="l00539"></a><span class="lineno"> 539</span> <span class="keyword"> </span>{</div>
|
|
<div class="line"><a name="l00540"></a><span class="lineno"> 540</span>  <span class="keywordtype">float</span> xi = Codec::decode_component (code, i);</div>
|
|
<div class="line"><a name="l00541"></a><span class="lineno"> 541</span>  <span class="keywordflow">return</span> vmin[i] + xi * vdiff[i];</div>
|
|
<div class="line"><a name="l00542"></a><span class="lineno"> 542</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> <span class="preprocessor">#ifdef USE_AVX</span></div>
|
|
<div class="line"><a name="l00545"></a><span class="lineno"> 545</span> <span class="preprocessor"></span> __m256 reconstruct_8_components (<span class="keyword">const</span> uint8_t * code, <span class="keywordtype">int</span> i)<span class="keyword"> const</span></div>
|
|
<div class="line"><a name="l00546"></a><span class="lineno"> 546</span> <span class="keyword"> </span>{</div>
|
|
<div class="line"><a name="l00547"></a><span class="lineno"> 547</span>  __m256 xi = Codec::decode_8_components (code, i);</div>
|
|
<div class="line"><a name="l00548"></a><span class="lineno"> 548</span>  <span class="keywordflow">return</span> _mm256_loadu_ps(vmin + i) + xi * _mm256_loadu_ps (vdiff + i);</div>
|
|
<div class="line"><a name="l00549"></a><span class="lineno"> 549</span>  }</div>
|
|
<div class="line"><a name="l00550"></a><span class="lineno"> 550</span> <span class="preprocessor">#endif</span></div>
|
|
<div class="line"><a name="l00551"></a><span class="lineno"> 551</span> <span class="preprocessor"></span></div>
|
|
<div class="line"><a name="l00552"></a><span class="lineno"> 552</span>  <span class="keywordtype">float</span> compute_distance_L2(SimilarityL2& sim, <span class="keyword">const</span> uint8_t* codes)<span class="keyword"></span></div>
|
|
<div class="line"><a name="l00553"></a><span class="lineno"> 553</span> <span class="keyword"> const override </span>{</div>
|
|
<div class="line"><a name="l00554"></a><span class="lineno"> 554</span>  <span class="keywordflow">return</span> compute_distance(*<span class="keyword">this</span>, sim, codes);</div>
|
|
<div class="line"><a name="l00555"></a><span class="lineno"> 555</span>  }</div>
|
|
<div class="line"><a name="l00556"></a><span class="lineno"> 556</span> </div>
|
|
<div class="line"><a name="l00557"></a><span class="lineno"> 557</span>  <span class="keywordtype">float</span> compute_distance_IP(SimilarityIP& sim, <span class="keyword">const</span> uint8_t* codes)<span class="keyword"></span></div>
|
|
<div class="line"><a name="l00558"></a><span class="lineno"> 558</span> <span class="keyword"> const override </span>{</div>
|
|
<div class="line"><a name="l00559"></a><span class="lineno"> 559</span>  <span class="keywordflow">return</span> compute_distance(*<span class="keyword">this</span>, sim, codes);</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> };</div>
|
|
<div class="line"><a name="l00562"></a><span class="lineno"> 562</span> </div>
|
|
<div class="line"><a name="l00563"></a><span class="lineno"> 563</span> <span class="preprocessor">#ifdef USE_AVX</span></div>
|
|
<div class="line"><a name="l00564"></a><span class="lineno"> 564</span> <span class="preprocessor"></span><span class="keyword">template</span><<span class="keyword">class</span> Codec></div>
|
|
<div class="line"><a name="l00565"></a><span class="lineno"> 565</span> <span class="keyword">struct </span>QuantizerNonUniform8: QuantizerNonUniform<Codec> {</div>
|
|
<div class="line"><a name="l00566"></a><span class="lineno"> 566</span> </div>
|
|
<div class="line"><a name="l00567"></a><span class="lineno"> 567</span>  QuantizerNonUniform8 (<span class="keywordtype">size_t</span> d, <span class="keyword">const</span> std::vector<float> &trained):</div>
|
|
<div class="line"><a name="l00568"></a><span class="lineno"> 568</span>  QuantizerNonUniform<Codec> (d, trained) {}</div>
|
|
<div class="line"><a name="l00569"></a><span class="lineno"> 569</span> </div>
|
|
<div class="line"><a name="l00570"></a><span class="lineno"> 570</span>  <span class="keywordtype">float</span> compute_distance_L2(SimilarityL2& sim, <span class="keyword">const</span> uint8_t* codes)<span class="keyword"></span></div>
|
|
<div class="line"><a name="l00571"></a><span class="lineno"> 571</span> <span class="keyword"> const override </span>{</div>
|
|
<div class="line"><a name="l00572"></a><span class="lineno"> 572</span>  <span class="keywordflow">return</span> compute_distance_8(*<span class="keyword">this</span>, sim, codes);</div>
|
|
<div class="line"><a name="l00573"></a><span class="lineno"> 573</span>  }</div>
|
|
<div class="line"><a name="l00574"></a><span class="lineno"> 574</span> </div>
|
|
<div class="line"><a name="l00575"></a><span class="lineno"> 575</span>  <span class="keywordtype">float</span> compute_distance_IP(SimilarityIP& sim, <span class="keyword">const</span> uint8_t* codes)<span class="keyword"></span></div>
|
|
<div class="line"><a name="l00576"></a><span class="lineno"> 576</span> <span class="keyword"> const override </span>{</div>
|
|
<div class="line"><a name="l00577"></a><span class="lineno"> 577</span>  <span class="keywordflow">return</span> compute_distance_8(*<span class="keyword">this</span>, sim, codes);</div>
|
|
<div class="line"><a name="l00578"></a><span class="lineno"> 578</span>  }</div>
|
|
<div class="line"><a name="l00579"></a><span class="lineno"> 579</span> };</div>
|
|
<div class="line"><a name="l00580"></a><span class="lineno"> 580</span> <span class="preprocessor">#endif</span></div>
|
|
<div class="line"><a name="l00581"></a><span class="lineno"> 581</span> <span class="preprocessor"></span></div>
|
|
<div class="line"><a name="l00582"></a><span class="lineno"> 582</span> </div>
|
|
<div class="line"><a name="l00583"></a><span class="lineno"> 583</span> </div>
|
|
<div class="line"><a name="l00584"></a><span class="lineno"> 584</span> </div>
|
|
<div class="line"><a name="l00585"></a><span class="lineno"> 585</span> </div>
|
|
<div class="line"><a name="l00586"></a><span class="lineno"> 586</span> Quantizer *select_quantizer (</div>
|
|
<div class="line"><a name="l00587"></a><span class="lineno"> 587</span>  QuantizerType qtype,</div>
|
|
<div class="line"><a name="l00588"></a><span class="lineno"> 588</span>  <span class="keywordtype">size_t</span> d, <span class="keyword">const</span> std::vector<float> & trained)</div>
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|
<div class="line"><a name="l00589"></a><span class="lineno"> 589</span> {</div>
|
|
<div class="line"><a name="l00590"></a><span class="lineno"> 590</span> <span class="preprocessor">#ifdef USE_AVX</span></div>
|
|
<div class="line"><a name="l00591"></a><span class="lineno"> 591</span> <span class="preprocessor"></span> <span class="keywordflow">if</span> (d % 8 == 0) {</div>
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|
<div class="line"><a name="l00592"></a><span class="lineno"> 592</span>  <span class="keywordflow">switch</span>(qtype) {</div>
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|
<div class="line"><a name="l00593"></a><span class="lineno"> 593</span>  <span class="keywordflow">case</span> <a class="code" href="structfaiss_1_1ScalarQuantizer.html#a1201dbd1611fa5c10782ade5d0e4952ea1650389e3efa052ff60177d502328a2c">ScalarQuantizer::QT_8bit</a>:</div>
|
|
<div class="line"><a name="l00594"></a><span class="lineno"> 594</span>  <span class="keywordflow">return</span> <span class="keyword">new</span> QuantizerNonUniform8<Codec8bit>(d, trained);</div>
|
|
<div class="line"><a name="l00595"></a><span class="lineno"> 595</span>  <span class="keywordflow">case</span> <a class="code" href="structfaiss_1_1ScalarQuantizer.html#a1201dbd1611fa5c10782ade5d0e4952eacd3d1bd71533a7bc52149e4b3d1db13b">ScalarQuantizer::QT_4bit</a>:</div>
|
|
<div class="line"><a name="l00596"></a><span class="lineno"> 596</span>  <span class="keywordflow">return</span> <span class="keyword">new</span> QuantizerNonUniform8<Codec4bit>(d, trained);</div>
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|
<div class="line"><a name="l00597"></a><span class="lineno"> 597</span>  <span class="keywordflow">case</span> <a class="code" href="structfaiss_1_1ScalarQuantizer.html#a1201dbd1611fa5c10782ade5d0e4952ea029f07a15ea64e7e73daaf9633ac429a">ScalarQuantizer::QT_8bit_uniform</a>:</div>
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|
<div class="line"><a name="l00598"></a><span class="lineno"> 598</span>  <span class="keywordflow">return</span> <span class="keyword">new</span> QuantizerUniform8<Codec8bit>(d, trained);</div>
|
|
<div class="line"><a name="l00599"></a><span class="lineno"> 599</span>  <span class="keywordflow">case</span> ScalarQuantizer::QT_4bit_uniform:</div>
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|
<div class="line"><a name="l00600"></a><span class="lineno"> 600</span>  <span class="keywordflow">return</span> <span class="keyword">new</span> QuantizerUniform8<Codec4bit>(d, trained);</div>
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|
<div class="line"><a name="l00601"></a><span class="lineno"> 601</span>  }</div>
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|
<div class="line"><a name="l00602"></a><span class="lineno"> 602</span>  } <span class="keywordflow">else</span></div>
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|
<div class="line"><a name="l00603"></a><span class="lineno"> 603</span> <span class="preprocessor">#endif</span></div>
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|
<div class="line"><a name="l00604"></a><span class="lineno"> 604</span> <span class="preprocessor"></span> {</div>
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<div class="line"><a name="l00605"></a><span class="lineno"> 605</span>  <span class="keywordflow">switch</span>(qtype) {</div>
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|
<div class="line"><a name="l00606"></a><span class="lineno"> 606</span>  <span class="keywordflow">case</span> <a class="code" href="structfaiss_1_1ScalarQuantizer.html#a1201dbd1611fa5c10782ade5d0e4952ea1650389e3efa052ff60177d502328a2c">ScalarQuantizer::QT_8bit</a>:</div>
|
|
<div class="line"><a name="l00607"></a><span class="lineno"> 607</span>  <span class="keywordflow">return</span> <span class="keyword">new</span> QuantizerNonUniform<Codec8bit>(d, trained);</div>
|
|
<div class="line"><a name="l00608"></a><span class="lineno"> 608</span>  <span class="keywordflow">case</span> <a class="code" href="structfaiss_1_1ScalarQuantizer.html#a1201dbd1611fa5c10782ade5d0e4952eacd3d1bd71533a7bc52149e4b3d1db13b">ScalarQuantizer::QT_4bit</a>:</div>
|
|
<div class="line"><a name="l00609"></a><span class="lineno"> 609</span>  <span class="keywordflow">return</span> <span class="keyword">new</span> QuantizerNonUniform<Codec4bit>(d, trained);</div>
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|
<div class="line"><a name="l00610"></a><span class="lineno"> 610</span>  <span class="keywordflow">case</span> <a class="code" href="structfaiss_1_1ScalarQuantizer.html#a1201dbd1611fa5c10782ade5d0e4952ea029f07a15ea64e7e73daaf9633ac429a">ScalarQuantizer::QT_8bit_uniform</a>:</div>
|
|
<div class="line"><a name="l00611"></a><span class="lineno"> 611</span>  <span class="keywordflow">return</span> <span class="keyword">new</span> QuantizerUniform<Codec8bit>(d, trained);</div>
|
|
<div class="line"><a name="l00612"></a><span class="lineno"> 612</span>  <span class="keywordflow">case</span> ScalarQuantizer::QT_4bit_uniform:</div>
|
|
<div class="line"><a name="l00613"></a><span class="lineno"> 613</span>  <span class="keywordflow">return</span> <span class="keyword">new</span> QuantizerUniform<Codec4bit>(d, trained);</div>
|
|
<div class="line"><a name="l00614"></a><span class="lineno"> 614</span>  }</div>
|
|
<div class="line"><a name="l00615"></a><span class="lineno"> 615</span>  }</div>
|
|
<div class="line"><a name="l00616"></a><span class="lineno"> 616</span>  FAISS_THROW_MSG (<span class="stringliteral">"unknown qtype"</span>);</div>
|
|
<div class="line"><a name="l00617"></a><span class="lineno"> 617</span>  <span class="keywordflow">return</span> <span class="keyword">nullptr</span>;</div>
|
|
<div class="line"><a name="l00618"></a><span class="lineno"> 618</span> }</div>
|
|
<div class="line"><a name="l00619"></a><span class="lineno"> 619</span> </div>
|
|
<div class="line"><a name="l00620"></a><span class="lineno"> 620</span> Quantizer *select_quantizer (<span class="keyword">const</span> ScalarQuantizer &sq)</div>
|
|
<div class="line"><a name="l00621"></a><span class="lineno"> 621</span> {</div>
|
|
<div class="line"><a name="l00622"></a><span class="lineno"> 622</span>  <span class="keywordflow">return</span> select_quantizer (sq.qtype, sq.d, sq.trained);</div>
|
|
<div class="line"><a name="l00623"></a><span class="lineno"> 623</span> }</div>
|
|
<div class="line"><a name="l00624"></a><span class="lineno"> 624</span> </div>
|
|
<div class="line"><a name="l00625"></a><span class="lineno"> 625</span> </div>
|
|
<div class="line"><a name="l00626"></a><span class="lineno"> 626</span> } <span class="comment">// anonymous namespace</span></div>
|
|
<div class="line"><a name="l00627"></a><span class="lineno"> 627</span> </div>
|
|
<div class="line"><a name="l00628"></a><span class="lineno"> 628</span> </div>
|
|
<div class="line"><a name="l00629"></a><span class="lineno"> 629</span> </div>
|
|
<div class="line"><a name="l00630"></a><span class="lineno"> 630</span> <span class="comment">/*******************************************************************</span></div>
|
|
<div class="line"><a name="l00631"></a><span class="lineno"> 631</span> <span class="comment"> * ScalarQuantizer implementation</span></div>
|
|
<div class="line"><a name="l00632"></a><span class="lineno"> 632</span> <span class="comment"> ********************************************************************/</span></div>
|
|
<div class="line"><a name="l00633"></a><span class="lineno"> 633</span> </div>
|
|
<div class="line"><a name="l00634"></a><span class="lineno"> 634</span> ScalarQuantizer::ScalarQuantizer</div>
|
|
<div class="line"><a name="l00635"></a><span class="lineno"> 635</span>  (<span class="keywordtype">size_t</span> d, QuantizerType qtype):</div>
|
|
<div class="line"><a name="l00636"></a><span class="lineno"> 636</span>  qtype (qtype), rangestat(RS_minmax), rangestat_arg(0), d (d)</div>
|
|
<div class="line"><a name="l00637"></a><span class="lineno"> 637</span> {</div>
|
|
<div class="line"><a name="l00638"></a><span class="lineno"> 638</span>  <span class="keywordflow">switch</span> (qtype) {</div>
|
|
<div class="line"><a name="l00639"></a><span class="lineno"> 639</span>  <span class="keywordflow">case</span> QT_8bit: <span class="keywordflow">case</span> QT_8bit_uniform:</div>
|
|
<div class="line"><a name="l00640"></a><span class="lineno"> 640</span>  code_size = <a class="code" href="structfaiss_1_1Index.html#a2a002388d2c081c2dbab8508dcefe73d">d</a>;</div>
|
|
<div class="line"><a name="l00641"></a><span class="lineno"> 641</span>  <span class="keywordflow">break</span>;</div>
|
|
<div class="line"><a name="l00642"></a><span class="lineno"> 642</span>  <span class="keywordflow">case</span> QT_4bit: <span class="keywordflow">case</span> QT_4bit_uniform:</div>
|
|
<div class="line"><a name="l00643"></a><span class="lineno"> 643</span>  code_size = (d + 1) / 2;</div>
|
|
<div class="line"><a name="l00644"></a><span class="lineno"> 644</span>  <span class="keywordflow">break</span>;</div>
|
|
<div class="line"><a name="l00645"></a><span class="lineno"> 645</span>  }</div>
|
|
<div class="line"><a name="l00646"></a><span class="lineno"> 646</span> </div>
|
|
<div class="line"><a name="l00647"></a><span class="lineno"> 647</span> }</div>
|
|
<div class="line"><a name="l00648"></a><span class="lineno"> 648</span> </div>
|
|
<div class="line"><a name="l00649"></a><span class="lineno"> 649</span> ScalarQuantizer::ScalarQuantizer ():</div>
|
|
<div class="line"><a name="l00650"></a><span class="lineno"> 650</span>  qtype(QT_8bit),</div>
|
|
<div class="line"><a name="l00651"></a><span class="lineno"> 651</span>  rangestat(RS_minmax), rangestat_arg(0), d (0), code_size(0)</div>
|
|
<div class="line"><a name="l00652"></a><span class="lineno"> 652</span> {}</div>
|
|
<div class="line"><a name="l00653"></a><span class="lineno"> 653</span> </div>
|
|
<div class="line"><a name="l00654"></a><span class="lineno"> 654</span> <span class="keywordtype">void</span> ScalarQuantizer::train (<span class="keywordtype">size_t</span> n, <span class="keyword">const</span> <span class="keywordtype">float</span> *x)</div>
|
|
<div class="line"><a name="l00655"></a><span class="lineno"> 655</span> {</div>
|
|
<div class="line"><a name="l00656"></a><span class="lineno"> 656</span>  <span class="keywordtype">int</span> bit_per_dim =</div>
|
|
<div class="line"><a name="l00657"></a><span class="lineno"> 657</span>  qtype == QT_4bit_uniform ? 4 :</div>
|
|
<div class="line"><a name="l00658"></a><span class="lineno"> 658</span>  qtype == <a class="code" href="structfaiss_1_1ScalarQuantizer.html#a1201dbd1611fa5c10782ade5d0e4952eacd3d1bd71533a7bc52149e4b3d1db13b">QT_4bit</a> ? 4 :</div>
|
|
<div class="line"><a name="l00659"></a><span class="lineno"> 659</span>  qtype == <a class="code" href="structfaiss_1_1ScalarQuantizer.html#a1201dbd1611fa5c10782ade5d0e4952ea029f07a15ea64e7e73daaf9633ac429a">QT_8bit_uniform</a> ? 8 :</div>
|
|
<div class="line"><a name="l00660"></a><span class="lineno"> 660</span>  qtype == <a class="code" href="structfaiss_1_1ScalarQuantizer.html#a1201dbd1611fa5c10782ade5d0e4952ea1650389e3efa052ff60177d502328a2c">QT_8bit</a> ? 8 : -1;</div>
|
|
<div class="line"><a name="l00661"></a><span class="lineno"> 661</span> </div>
|
|
<div class="line"><a name="l00662"></a><span class="lineno"> 662</span>  <span class="keywordflow">switch</span> (qtype) {</div>
|
|
<div class="line"><a name="l00663"></a><span class="lineno"> 663</span>  <span class="keywordflow">case</span> QT_4bit_uniform: <span class="keywordflow">case</span> <a class="code" href="structfaiss_1_1ScalarQuantizer.html#a1201dbd1611fa5c10782ade5d0e4952ea029f07a15ea64e7e73daaf9633ac429a">QT_8bit_uniform</a>:</div>
|
|
<div class="line"><a name="l00664"></a><span class="lineno"> 664</span>  train_Uniform (rangestat, rangestat_arg,</div>
|
|
<div class="line"><a name="l00665"></a><span class="lineno"> 665</span>  n * d, 1 << bit_per_dim, x, trained);</div>
|
|
<div class="line"><a name="l00666"></a><span class="lineno"> 666</span>  <span class="keywordflow">break</span>;</div>
|
|
<div class="line"><a name="l00667"></a><span class="lineno"> 667</span>  <span class="keywordflow">case</span> <a class="code" href="structfaiss_1_1ScalarQuantizer.html#a1201dbd1611fa5c10782ade5d0e4952eacd3d1bd71533a7bc52149e4b3d1db13b">QT_4bit</a>: <span class="keywordflow">case</span> <a class="code" href="structfaiss_1_1ScalarQuantizer.html#a1201dbd1611fa5c10782ade5d0e4952ea1650389e3efa052ff60177d502328a2c">QT_8bit</a>:</div>
|
|
<div class="line"><a name="l00668"></a><span class="lineno"> 668</span>  train_NonUniform (rangestat, rangestat_arg,</div>
|
|
<div class="line"><a name="l00669"></a><span class="lineno"> 669</span>  n, d, 1 << bit_per_dim, x, trained);</div>
|
|
<div class="line"><a name="l00670"></a><span class="lineno"> 670</span>  <span class="keywordflow">break</span>;</div>
|
|
<div class="line"><a name="l00671"></a><span class="lineno"> 671</span>  }</div>
|
|
<div class="line"><a name="l00672"></a><span class="lineno"> 672</span> }</div>
|
|
<div class="line"><a name="l00673"></a><span class="lineno"> 673</span> </div>
|
|
<div class="line"><a name="l00674"></a><span class="lineno"><a class="line" href="structfaiss_1_1ScalarQuantizer.html#a2bccf276565c4f80fed3d0c715c58816"> 674</a></span> <span class="keywordtype">void</span> <a class="code" href="structfaiss_1_1ScalarQuantizer.html#a2bccf276565c4f80fed3d0c715c58816">ScalarQuantizer::compute_codes</a> (<span class="keyword">const</span> <span class="keywordtype">float</span> * x,</div>
|
|
<div class="line"><a name="l00675"></a><span class="lineno"> 675</span>  uint8_t * codes,</div>
|
|
<div class="line"><a name="l00676"></a><span class="lineno"> 676</span>  <span class="keywordtype">size_t</span> n)<span class="keyword"> const</span></div>
|
|
<div class="line"><a name="l00677"></a><span class="lineno"> 677</span> <span class="keyword"></span>{</div>
|
|
<div class="line"><a name="l00678"></a><span class="lineno"> 678</span>  Quantizer *squant = select_quantizer (*<span class="keyword">this</span>);</div>
|
|
<div class="line"><a name="l00679"></a><span class="lineno"> 679</span>  <a class="code" href="structfaiss_1_1ScopeDeleter1.html">ScopeDeleter1<Quantizer></a> del(squant);</div>
|
|
<div class="line"><a name="l00680"></a><span class="lineno"> 680</span> <span class="preprocessor">#pragma omp parallel for</span></div>
|
|
<div class="line"><a name="l00681"></a><span class="lineno"> 681</span> <span class="preprocessor"></span> <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < n; i++)</div>
|
|
<div class="line"><a name="l00682"></a><span class="lineno"> 682</span>  squant->encode_vector (x + i * d, codes + i * <a class="code" href="structfaiss_1_1ScalarQuantizer.html#a647b8774e4cd8ca5623a194f5c7f8a33">code_size</a>);</div>
|
|
<div class="line"><a name="l00683"></a><span class="lineno"> 683</span> }</div>
|
|
<div class="line"><a name="l00684"></a><span class="lineno"> 684</span> </div>
|
|
<div class="line"><a name="l00685"></a><span class="lineno"><a class="line" href="structfaiss_1_1ScalarQuantizer.html#a7ab9e9158da1777d45e6f9bf73bfd489"> 685</a></span> <span class="keywordtype">void</span> <a class="code" href="structfaiss_1_1ScalarQuantizer.html#a7ab9e9158da1777d45e6f9bf73bfd489">ScalarQuantizer::decode</a> (<span class="keyword">const</span> uint8_t *codes, <span class="keywordtype">float</span> *x, <span class="keywordtype">size_t</span> n)<span class="keyword"> const</span></div>
|
|
<div class="line"><a name="l00686"></a><span class="lineno"> 686</span> <span class="keyword"></span>{</div>
|
|
<div class="line"><a name="l00687"></a><span class="lineno"> 687</span>  Quantizer *squant = select_quantizer (*<span class="keyword">this</span>);</div>
|
|
<div class="line"><a name="l00688"></a><span class="lineno"> 688</span>  <a class="code" href="structfaiss_1_1ScopeDeleter1.html">ScopeDeleter1<Quantizer></a> del(squant);</div>
|
|
<div class="line"><a name="l00689"></a><span class="lineno"> 689</span> <span class="preprocessor">#pragma omp parallel for</span></div>
|
|
<div class="line"><a name="l00690"></a><span class="lineno"> 690</span> <span class="preprocessor"></span> <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < n; i++)</div>
|
|
<div class="line"><a name="l00691"></a><span class="lineno"> 691</span>  squant->decode_vector (codes + i * <a class="code" href="structfaiss_1_1ScalarQuantizer.html#a647b8774e4cd8ca5623a194f5c7f8a33">code_size</a>, x + i * d);</div>
|
|
<div class="line"><a name="l00692"></a><span class="lineno"> 692</span> }</div>
|
|
<div class="line"><a name="l00693"></a><span class="lineno"> 693</span> </div>
|
|
<div class="line"><a name="l00694"></a><span class="lineno"> 694</span> <span class="comment">/*******************************************************************</span></div>
|
|
<div class="line"><a name="l00695"></a><span class="lineno"> 695</span> <span class="comment"> * IndexScalarQuantizer implementation</span></div>
|
|
<div class="line"><a name="l00696"></a><span class="lineno"> 696</span> <span class="comment"> ********************************************************************/</span></div>
|
|
<div class="line"><a name="l00697"></a><span class="lineno"> 697</span> </div>
|
|
<div class="line"><a name="l00698"></a><span class="lineno"> 698</span> IndexScalarQuantizer::IndexScalarQuantizer</div>
|
|
<div class="line"><a name="l00699"></a><span class="lineno"><a class="line" href="structfaiss_1_1IndexScalarQuantizer.html#a474ad5a50eb2e9f0d79f869855c57223"> 699</a></span>  (<span class="keywordtype">int</span> d, <a class="code" href="structfaiss_1_1ScalarQuantizer.html#a1201dbd1611fa5c10782ade5d0e4952e">ScalarQuantizer::QuantizerType</a> qtype,</div>
|
|
<div class="line"><a name="l00700"></a><span class="lineno"> 700</span>  <a class="code" href="namespacefaiss.html#afd12191c638da74760ff397cf319752c">MetricType</a> metric):</div>
|
|
<div class="line"><a name="l00701"></a><span class="lineno"> 701</span>  <a class="code" href="structfaiss_1_1Index.html">Index</a>(d, metric),</div>
|
|
<div class="line"><a name="l00702"></a><span class="lineno"> 702</span>  sq (d, qtype)</div>
|
|
<div class="line"><a name="l00703"></a><span class="lineno"> 703</span> {</div>
|
|
<div class="line"><a name="l00704"></a><span class="lineno"> 704</span>  is_trained = <span class="keyword">false</span>;</div>
|
|
<div class="line"><a name="l00705"></a><span class="lineno"> 705</span>  code_size = sq.code_size;</div>
|
|
<div class="line"><a name="l00706"></a><span class="lineno"> 706</span> }</div>
|
|
<div class="line"><a name="l00707"></a><span class="lineno"> 707</span> </div>
|
|
<div class="line"><a name="l00708"></a><span class="lineno"> 708</span> </div>
|
|
<div class="line"><a name="l00709"></a><span class="lineno"> 709</span> IndexScalarQuantizer::IndexScalarQuantizer ():</div>
|
|
<div class="line"><a name="l00710"></a><span class="lineno"> 710</span>  <a class="code" href="structfaiss_1_1IndexScalarQuantizer.html">IndexScalarQuantizer</a>(0, <a class="code" href="structfaiss_1_1ScalarQuantizer.html">ScalarQuantizer</a>::QT_8bit)</div>
|
|
<div class="line"><a name="l00711"></a><span class="lineno"> 711</span> {}</div>
|
|
<div class="line"><a name="l00712"></a><span class="lineno"> 712</span> </div>
|
|
<div class="line"><a name="l00713"></a><span class="lineno"><a class="line" href="structfaiss_1_1IndexScalarQuantizer.html#a300647e9cdac9acd160f2c55c610056b"> 713</a></span> <span class="keywordtype">void</span> <a class="code" href="structfaiss_1_1IndexScalarQuantizer.html#a300647e9cdac9acd160f2c55c610056b">IndexScalarQuantizer::train</a>(idx_t n, <span class="keyword">const</span> <span class="keywordtype">float</span>* x)</div>
|
|
<div class="line"><a name="l00714"></a><span class="lineno"> 714</span> {</div>
|
|
<div class="line"><a name="l00715"></a><span class="lineno"> 715</span>  <a class="code" href="structfaiss_1_1IndexScalarQuantizer.html#a71381f74754d8a54812e80af46a2a83a">sq</a>.train(n, x);</div>
|
|
<div class="line"><a name="l00716"></a><span class="lineno"> 716</span>  <a class="code" href="structfaiss_1_1Index.html#a6e92732617c4dbe364e7678dd8773a7f">is_trained</a> = <span class="keyword">true</span>;</div>
|
|
<div class="line"><a name="l00717"></a><span class="lineno"> 717</span> }</div>
|
|
<div class="line"><a name="l00718"></a><span class="lineno"> 718</span> </div>
|
|
<div class="line"><a name="l00719"></a><span class="lineno"><a class="line" href="structfaiss_1_1IndexScalarQuantizer.html#ad49602f9ecfcaa2ec8737a449b69ccd7"> 719</a></span> <span class="keywordtype">void</span> <a class="code" href="structfaiss_1_1IndexScalarQuantizer.html#ad49602f9ecfcaa2ec8737a449b69ccd7">IndexScalarQuantizer::add</a>(idx_t n, <span class="keyword">const</span> <span class="keywordtype">float</span>* x)</div>
|
|
<div class="line"><a name="l00720"></a><span class="lineno"> 720</span> {</div>
|
|
<div class="line"><a name="l00721"></a><span class="lineno"> 721</span>  FAISS_THROW_IF_NOT (<a class="code" href="structfaiss_1_1Index.html#a6e92732617c4dbe364e7678dd8773a7f">is_trained</a>);</div>
|
|
<div class="line"><a name="l00722"></a><span class="lineno"> 722</span>  <a class="code" href="structfaiss_1_1IndexScalarQuantizer.html#a861fa059f9d4ced9147e08193a2be9be">codes</a>.resize ((n + <a class="code" href="structfaiss_1_1Index.html#a6970683faa021b7a6f1a0865c0d4eccd">ntotal</a>) * code_size);</div>
|
|
<div class="line"><a name="l00723"></a><span class="lineno"> 723</span>  <a class="code" href="structfaiss_1_1IndexScalarQuantizer.html#a71381f74754d8a54812e80af46a2a83a">sq</a>.<a class="code" href="structfaiss_1_1ScalarQuantizer.html#a2bccf276565c4f80fed3d0c715c58816">compute_codes</a> (x, &<a class="code" href="structfaiss_1_1IndexScalarQuantizer.html#a861fa059f9d4ced9147e08193a2be9be">codes</a>[<a class="code" href="structfaiss_1_1Index.html#a6970683faa021b7a6f1a0865c0d4eccd">ntotal</a> * code_size], n);</div>
|
|
<div class="line"><a name="l00724"></a><span class="lineno"> 724</span>  <a class="code" href="structfaiss_1_1Index.html#a6970683faa021b7a6f1a0865c0d4eccd">ntotal</a> += n;</div>
|
|
<div class="line"><a name="l00725"></a><span class="lineno"> 725</span> }</div>
|
|
<div class="line"><a name="l00726"></a><span class="lineno"> 726</span> </div>
|
|
<div class="line"><a name="l00727"></a><span class="lineno"><a class="line" href="structfaiss_1_1IndexScalarQuantizer.html#abf24732c29106bb808148c3d30599662"> 727</a></span> <span class="keywordtype">void</span> <a class="code" href="structfaiss_1_1IndexScalarQuantizer.html#abf24732c29106bb808148c3d30599662">IndexScalarQuantizer::search</a>(</div>
|
|
<div class="line"><a name="l00728"></a><span class="lineno"> 728</span>  idx_t n,</div>
|
|
<div class="line"><a name="l00729"></a><span class="lineno"> 729</span>  <span class="keyword">const</span> <span class="keywordtype">float</span>* x,</div>
|
|
<div class="line"><a name="l00730"></a><span class="lineno"> 730</span>  idx_t k,</div>
|
|
<div class="line"><a name="l00731"></a><span class="lineno"> 731</span>  <span class="keywordtype">float</span>* distances,</div>
|
|
<div class="line"><a name="l00732"></a><span class="lineno"> 732</span>  idx_t* labels)<span class="keyword"> const</span></div>
|
|
<div class="line"><a name="l00733"></a><span class="lineno"> 733</span> <span class="keyword"></span>{</div>
|
|
<div class="line"><a name="l00734"></a><span class="lineno"> 734</span>  Quantizer *squant = select_quantizer (<a class="code" href="structfaiss_1_1IndexScalarQuantizer.html#a71381f74754d8a54812e80af46a2a83a">sq</a>);</div>
|
|
<div class="line"><a name="l00735"></a><span class="lineno"> 735</span>  <a class="code" href="structfaiss_1_1ScopeDeleter1.html">ScopeDeleter1<Quantizer></a> del(squant);</div>
|
|
<div class="line"><a name="l00736"></a><span class="lineno"> 736</span>  FAISS_THROW_IF_NOT (<a class="code" href="structfaiss_1_1Index.html#a6e92732617c4dbe364e7678dd8773a7f">is_trained</a>);</div>
|
|
<div class="line"><a name="l00737"></a><span class="lineno"> 737</span> </div>
|
|
<div class="line"><a name="l00738"></a><span class="lineno"> 738</span>  <span class="keywordflow">if</span> (<a class="code" href="structfaiss_1_1Index.html#a8e18f641854b2bde83ecff0a2f9a6f4e">metric_type</a> == METRIC_INNER_PRODUCT) {</div>
|
|
<div class="line"><a name="l00739"></a><span class="lineno"> 739</span> <span class="preprocessor">#pragma omp parallel for</span></div>
|
|
<div class="line"><a name="l00740"></a><span class="lineno"> 740</span> <span class="preprocessor"></span> <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < n; i++) {</div>
|
|
<div class="line"><a name="l00741"></a><span class="lineno"> 741</span>  idx_t *idxi = labels + i * k;</div>
|
|
<div class="line"><a name="l00742"></a><span class="lineno"> 742</span>  <span class="keywordtype">float</span> *simi = distances + i * k;</div>
|
|
<div class="line"><a name="l00743"></a><span class="lineno"> 743</span>  minheap_heapify (k, simi, idxi);</div>
|
|
<div class="line"><a name="l00744"></a><span class="lineno"> 744</span> </div>
|
|
<div class="line"><a name="l00745"></a><span class="lineno"> 745</span>  SimilarityIP sim(x + i * d, 0);</div>
|
|
<div class="line"><a name="l00746"></a><span class="lineno"> 746</span>  <span class="keyword">const</span> uint8_t *ci = <a class="code" href="structfaiss_1_1IndexScalarQuantizer.html#a861fa059f9d4ced9147e08193a2be9be">codes</a>.data ();</div>
|
|
<div class="line"><a name="l00747"></a><span class="lineno"> 747</span> </div>
|
|
<div class="line"><a name="l00748"></a><span class="lineno"> 748</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> j = 0; j < <a class="code" href="structfaiss_1_1Index.html#a6970683faa021b7a6f1a0865c0d4eccd">ntotal</a>; j++) {</div>
|
|
<div class="line"><a name="l00749"></a><span class="lineno"> 749</span>  <span class="keywordtype">float</span> accu = squant->compute_distance_IP(sim, ci);</div>
|
|
<div class="line"><a name="l00750"></a><span class="lineno"> 750</span> </div>
|
|
<div class="line"><a name="l00751"></a><span class="lineno"> 751</span>  <span class="keywordflow">if</span> (accu > simi [0]) {</div>
|
|
<div class="line"><a name="l00752"></a><span class="lineno"> 752</span>  minheap_pop (k, simi, idxi);</div>
|
|
<div class="line"><a name="l00753"></a><span class="lineno"> 753</span>  minheap_push (k, simi, idxi, accu, j);</div>
|
|
<div class="line"><a name="l00754"></a><span class="lineno"> 754</span>  }</div>
|
|
<div class="line"><a name="l00755"></a><span class="lineno"> 755</span>  ci += code_size;</div>
|
|
<div class="line"><a name="l00756"></a><span class="lineno"> 756</span>  }</div>
|
|
<div class="line"><a name="l00757"></a><span class="lineno"> 757</span>  minheap_reorder (k, simi, idxi);</div>
|
|
<div class="line"><a name="l00758"></a><span class="lineno"> 758</span>  }</div>
|
|
<div class="line"><a name="l00759"></a><span class="lineno"> 759</span>  } <span class="keywordflow">else</span> {</div>
|
|
<div class="line"><a name="l00760"></a><span class="lineno"> 760</span> <span class="preprocessor">#pragma omp parallel for</span></div>
|
|
<div class="line"><a name="l00761"></a><span class="lineno"> 761</span> <span class="preprocessor"></span> <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < n; i++) {</div>
|
|
<div class="line"><a name="l00762"></a><span class="lineno"> 762</span>  idx_t *idxi = labels + i * k;</div>
|
|
<div class="line"><a name="l00763"></a><span class="lineno"> 763</span>  <span class="keywordtype">float</span> *simi = distances + i * k;</div>
|
|
<div class="line"><a name="l00764"></a><span class="lineno"> 764</span>  maxheap_heapify (k, simi, idxi);</div>
|
|
<div class="line"><a name="l00765"></a><span class="lineno"> 765</span> </div>
|
|
<div class="line"><a name="l00766"></a><span class="lineno"> 766</span>  SimilarityL2 sim(x + i * d);</div>
|
|
<div class="line"><a name="l00767"></a><span class="lineno"> 767</span>  <span class="keyword">const</span> uint8_t *ci = <a class="code" href="structfaiss_1_1IndexScalarQuantizer.html#a861fa059f9d4ced9147e08193a2be9be">codes</a>.data ();</div>
|
|
<div class="line"><a name="l00768"></a><span class="lineno"> 768</span> </div>
|
|
<div class="line"><a name="l00769"></a><span class="lineno"> 769</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> j = 0; j < <a class="code" href="structfaiss_1_1Index.html#a6970683faa021b7a6f1a0865c0d4eccd">ntotal</a>; j++) {</div>
|
|
<div class="line"><a name="l00770"></a><span class="lineno"> 770</span>  <span class="keywordtype">float</span> accu = squant->compute_distance_L2(sim, ci);</div>
|
|
<div class="line"><a name="l00771"></a><span class="lineno"> 771</span> </div>
|
|
<div class="line"><a name="l00772"></a><span class="lineno"> 772</span>  <span class="keywordflow">if</span> (accu < simi [0]) {</div>
|
|
<div class="line"><a name="l00773"></a><span class="lineno"> 773</span>  maxheap_pop (k, simi, idxi);</div>
|
|
<div class="line"><a name="l00774"></a><span class="lineno"> 774</span>  maxheap_push (k, simi, idxi, accu, j);</div>
|
|
<div class="line"><a name="l00775"></a><span class="lineno"> 775</span>  }</div>
|
|
<div class="line"><a name="l00776"></a><span class="lineno"> 776</span>  ci += code_size;</div>
|
|
<div class="line"><a name="l00777"></a><span class="lineno"> 777</span>  }</div>
|
|
<div class="line"><a name="l00778"></a><span class="lineno"> 778</span>  maxheap_reorder (k, simi, idxi);</div>
|
|
<div class="line"><a name="l00779"></a><span class="lineno"> 779</span>  }</div>
|
|
<div class="line"><a name="l00780"></a><span class="lineno"> 780</span>  }</div>
|
|
<div class="line"><a name="l00781"></a><span class="lineno"> 781</span> </div>
|
|
<div class="line"><a name="l00782"></a><span class="lineno"> 782</span> }</div>
|
|
<div class="line"><a name="l00783"></a><span class="lineno"> 783</span> </div>
|
|
<div class="line"><a name="l00784"></a><span class="lineno"><a class="line" href="structfaiss_1_1IndexScalarQuantizer.html#af0d6b901a2a02fff34e5c7c1ea5b8d55"> 784</a></span> <span class="keywordtype">void</span> <a class="code" href="structfaiss_1_1IndexScalarQuantizer.html#af0d6b901a2a02fff34e5c7c1ea5b8d55">IndexScalarQuantizer::reset</a>()</div>
|
|
<div class="line"><a name="l00785"></a><span class="lineno"> 785</span> {</div>
|
|
<div class="line"><a name="l00786"></a><span class="lineno"> 786</span>  <a class="code" href="structfaiss_1_1IndexScalarQuantizer.html#a861fa059f9d4ced9147e08193a2be9be">codes</a>.clear();</div>
|
|
<div class="line"><a name="l00787"></a><span class="lineno"> 787</span>  <a class="code" href="structfaiss_1_1Index.html#a6970683faa021b7a6f1a0865c0d4eccd">ntotal</a> = 0;</div>
|
|
<div class="line"><a name="l00788"></a><span class="lineno"> 788</span> }</div>
|
|
<div class="line"><a name="l00789"></a><span class="lineno"> 789</span> </div>
|
|
<div class="line"><a name="l00790"></a><span class="lineno"><a class="line" href="structfaiss_1_1IndexScalarQuantizer.html#a06e6935b75f0b209f65fffa1c9e1477c"> 790</a></span> <span class="keywordtype">void</span> <a class="code" href="structfaiss_1_1IndexScalarQuantizer.html#a06e6935b75f0b209f65fffa1c9e1477c">IndexScalarQuantizer::reconstruct_n</a>(</div>
|
|
<div class="line"><a name="l00791"></a><span class="lineno"> 791</span>  idx_t i0, idx_t ni, <span class="keywordtype">float</span>* recons)<span class="keyword"> const</span></div>
|
|
<div class="line"><a name="l00792"></a><span class="lineno"> 792</span> <span class="keyword"></span>{</div>
|
|
<div class="line"><a name="l00793"></a><span class="lineno"> 793</span>  Quantizer *squant = select_quantizer (<a class="code" href="structfaiss_1_1IndexScalarQuantizer.html#a71381f74754d8a54812e80af46a2a83a">sq</a>);</div>
|
|
<div class="line"><a name="l00794"></a><span class="lineno"> 794</span>  <a class="code" href="structfaiss_1_1ScopeDeleter1.html">ScopeDeleter1<Quantizer></a> del (squant);</div>
|
|
<div class="line"><a name="l00795"></a><span class="lineno"> 795</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < ni; i++) {</div>
|
|
<div class="line"><a name="l00796"></a><span class="lineno"> 796</span>  squant->decode_vector(&<a class="code" href="structfaiss_1_1IndexScalarQuantizer.html#a861fa059f9d4ced9147e08193a2be9be">codes</a>[(i + i0) * code_size], recons + i * d);</div>
|
|
<div class="line"><a name="l00797"></a><span class="lineno"> 797</span>  }</div>
|
|
<div class="line"><a name="l00798"></a><span class="lineno"> 798</span> }</div>
|
|
<div class="line"><a name="l00799"></a><span class="lineno"> 799</span> </div>
|
|
<div class="line"><a name="l00800"></a><span class="lineno"><a class="line" href="structfaiss_1_1IndexScalarQuantizer.html#a8fb8680f64465d643d96119da58099f3"> 800</a></span> <span class="keywordtype">void</span> <a class="code" href="structfaiss_1_1IndexScalarQuantizer.html#a8fb8680f64465d643d96119da58099f3">IndexScalarQuantizer::reconstruct</a>(idx_t key, <span class="keywordtype">float</span>* recons)<span class="keyword"> const</span></div>
|
|
<div class="line"><a name="l00801"></a><span class="lineno"> 801</span> <span class="keyword"></span>{</div>
|
|
<div class="line"><a name="l00802"></a><span class="lineno"> 802</span>  <a class="code" href="structfaiss_1_1IndexScalarQuantizer.html#a06e6935b75f0b209f65fffa1c9e1477c">reconstruct_n</a>(key, 1, recons);</div>
|
|
<div class="line"><a name="l00803"></a><span class="lineno"> 803</span> }</div>
|
|
<div class="line"><a name="l00804"></a><span class="lineno"> 804</span> </div>
|
|
<div class="line"><a name="l00805"></a><span class="lineno"> 805</span> </div>
|
|
<div class="line"><a name="l00806"></a><span class="lineno"> 806</span> <span class="comment">/*******************************************************************</span></div>
|
|
<div class="line"><a name="l00807"></a><span class="lineno"> 807</span> <span class="comment"> * IndexIVFScalarQuantizer implementation</span></div>
|
|
<div class="line"><a name="l00808"></a><span class="lineno"> 808</span> <span class="comment"> ********************************************************************/</span></div>
|
|
<div class="line"><a name="l00809"></a><span class="lineno"> 809</span> </div>
|
|
<div class="line"><a name="l00810"></a><span class="lineno"> 810</span> IndexIVFScalarQuantizer::IndexIVFScalarQuantizer</div>
|
|
<div class="line"><a name="l00811"></a><span class="lineno"> 811</span>  (<a class="code" href="structfaiss_1_1Index.html">Index</a> *quantizer, <span class="keywordtype">size_t</span> d, <span class="keywordtype">size_t</span> nlist,</div>
|
|
<div class="line"><a name="l00812"></a><span class="lineno"> 812</span>  QuantizerType qtype, <a class="code" href="namespacefaiss.html#afd12191c638da74760ff397cf319752c">MetricType</a> metric):</div>
|
|
<div class="line"><a name="l00813"></a><span class="lineno"> 813</span>  <a class="code" href="structfaiss_1_1IndexIVF.html">IndexIVF</a> (quantizer, d, nlist, metric),</div>
|
|
<div class="line"><a name="l00814"></a><span class="lineno"> 814</span>  sq (d, qtype)</div>
|
|
<div class="line"><a name="l00815"></a><span class="lineno"> 815</span> {</div>
|
|
<div class="line"><a name="l00816"></a><span class="lineno"> 816</span>  code_size = <a class="code" href="structfaiss_1_1IndexScalarQuantizer.html#a71381f74754d8a54812e80af46a2a83a">sq</a>.<a class="code" href="structfaiss_1_1ScalarQuantizer.html#a647b8774e4cd8ca5623a194f5c7f8a33">code_size</a>;</div>
|
|
<div class="line"><a name="l00817"></a><span class="lineno"> 817</span>  <a class="code" href="structfaiss_1_1Index.html#a6e92732617c4dbe364e7678dd8773a7f">is_trained</a> = <span class="keyword">false</span>;</div>
|
|
<div class="line"><a name="l00818"></a><span class="lineno"> 818</span> }</div>
|
|
<div class="line"><a name="l00819"></a><span class="lineno"> 819</span> </div>
|
|
<div class="line"><a name="l00820"></a><span class="lineno"> 820</span> IndexIVFScalarQuantizer::IndexIVFScalarQuantizer ():</div>
|
|
<div class="line"><a name="l00821"></a><span class="lineno"> 821</span>  IndexIVF ()</div>
|
|
<div class="line"><a name="l00822"></a><span class="lineno"> 822</span> {}</div>
|
|
<div class="line"><a name="l00823"></a><span class="lineno"> 823</span> </div>
|
|
<div class="line"><a name="l00824"></a><span class="lineno"><a class="line" href="structfaiss_1_1IndexIVFScalarQuantizer.html#ac05d7fbfed59c85d1cf8ae526d279744"> 824</a></span> <span class="keywordtype">void</span> <a class="code" href="structfaiss_1_1IndexIVFScalarQuantizer.html#ac05d7fbfed59c85d1cf8ae526d279744">IndexIVFScalarQuantizer::train_residual</a> (idx_t n, <span class="keyword">const</span> <span class="keywordtype">float</span> *x)</div>
|
|
<div class="line"><a name="l00825"></a><span class="lineno"> 825</span> {</div>
|
|
<div class="line"><a name="l00826"></a><span class="lineno"> 826</span>  <span class="keywordtype">long</span> * idx = <span class="keyword">new</span> <span class="keywordtype">long</span> [n];</div>
|
|
<div class="line"><a name="l00827"></a><span class="lineno"> 827</span>  <a class="code" href="structfaiss_1_1ScopeDeleter.html">ScopeDeleter<long></a> del (idx);</div>
|
|
<div class="line"><a name="l00828"></a><span class="lineno"> 828</span>  <a class="code" href="structfaiss_1_1IndexIVF.html#a4b40cc7a70dff41196a3b8769586667a">quantizer</a>-><a class="code" href="structfaiss_1_1Index.html#a8bc5d8d1cd0dd7b34b3c98a9f76b4a9c">assign</a> (n, x, idx);</div>
|
|
<div class="line"><a name="l00829"></a><span class="lineno"> 829</span>  <span class="keywordtype">float</span> *residuals = <span class="keyword">new</span> <span class="keywordtype">float</span> [n * <a class="code" href="structfaiss_1_1Index.html#a2a002388d2c081c2dbab8508dcefe73d">d</a>];</div>
|
|
<div class="line"><a name="l00830"></a><span class="lineno"> 830</span>  <a class="code" href="structfaiss_1_1ScopeDeleter.html">ScopeDeleter<float></a> del2 (residuals);</div>
|
|
<div class="line"><a name="l00831"></a><span class="lineno"> 831</span> </div>
|
|
<div class="line"><a name="l00832"></a><span class="lineno"> 832</span> <span class="preprocessor">#pragma omp parallel for</span></div>
|
|
<div class="line"><a name="l00833"></a><span class="lineno"> 833</span> <span class="preprocessor"></span> <span class="keywordflow">for</span> (idx_t i = 0; i < n; i++) {</div>
|
|
<div class="line"><a name="l00834"></a><span class="lineno"> 834</span>  <a class="code" href="structfaiss_1_1IndexIVF.html#a4b40cc7a70dff41196a3b8769586667a">quantizer</a>-><a class="code" href="structfaiss_1_1Index.html#aaae77608bbda70b1098897e9167a82f9">compute_residual</a> (x + i * d, residuals + i * d, idx[i]);</div>
|
|
<div class="line"><a name="l00835"></a><span class="lineno"> 835</span>  }</div>
|
|
<div class="line"><a name="l00836"></a><span class="lineno"> 836</span> </div>
|
|
<div class="line"><a name="l00837"></a><span class="lineno"> 837</span>  sq.train (n, residuals);</div>
|
|
<div class="line"><a name="l00838"></a><span class="lineno"> 838</span> </div>
|
|
<div class="line"><a name="l00839"></a><span class="lineno"> 839</span> }</div>
|
|
<div class="line"><a name="l00840"></a><span class="lineno"> 840</span> </div>
|
|
<div class="line"><a name="l00841"></a><span class="lineno"> 841</span> </div>
|
|
<div class="line"><a name="l00842"></a><span class="lineno"> 842</span> <span class="keywordtype">void</span> <a class="code" href="structfaiss_1_1IndexIVFScalarQuantizer.html#afa95c17787b7e3dbed9309b440d4d748">IndexIVFScalarQuantizer::add_with_ids</a></div>
|
|
<div class="line"><a name="l00843"></a><span class="lineno"><a class="line" href="structfaiss_1_1IndexIVFScalarQuantizer.html#afa95c17787b7e3dbed9309b440d4d748"> 843</a></span>  (idx_t n, <span class="keyword">const</span> <span class="keywordtype">float</span> * x, <span class="keyword">const</span> <span class="keywordtype">long</span> *xids)</div>
|
|
<div class="line"><a name="l00844"></a><span class="lineno"> 844</span> {</div>
|
|
<div class="line"><a name="l00845"></a><span class="lineno"> 845</span>  FAISS_THROW_IF_NOT (is_trained);</div>
|
|
<div class="line"><a name="l00846"></a><span class="lineno"> 846</span>  <span class="keywordtype">long</span> * idx = <span class="keyword">new</span> <span class="keywordtype">long</span> [n];</div>
|
|
<div class="line"><a name="l00847"></a><span class="lineno"> 847</span>  <a class="code" href="structfaiss_1_1ScopeDeleter.html">ScopeDeleter<long></a> del (idx);</div>
|
|
<div class="line"><a name="l00848"></a><span class="lineno"> 848</span>  quantizer->assign (n, x, idx);</div>
|
|
<div class="line"><a name="l00849"></a><span class="lineno"> 849</span>  <span class="keywordtype">size_t</span> nadd = 0;</div>
|
|
<div class="line"><a name="l00850"></a><span class="lineno"> 850</span>  Quantizer *squant = select_quantizer (sq);</div>
|
|
<div class="line"><a name="l00851"></a><span class="lineno"> 851</span>  <a class="code" href="structfaiss_1_1ScopeDeleter1.html">ScopeDeleter1<Quantizer></a> del2 (squant);</div>
|
|
<div class="line"><a name="l00852"></a><span class="lineno"> 852</span> </div>
|
|
<div class="line"><a name="l00853"></a><span class="lineno"> 853</span> <span class="preprocessor">#pragma omp parallel reduction(+: nadd)</span></div>
|
|
<div class="line"><a name="l00854"></a><span class="lineno"> 854</span> <span class="preprocessor"></span> {</div>
|
|
<div class="line"><a name="l00855"></a><span class="lineno"> 855</span>  std::vector<float> residual (d);</div>
|
|
<div class="line"><a name="l00856"></a><span class="lineno"> 856</span>  <span class="keywordtype">int</span> nt = omp_get_num_threads();</div>
|
|
<div class="line"><a name="l00857"></a><span class="lineno"> 857</span>  <span class="keywordtype">int</span> rank = omp_get_thread_num();</div>
|
|
<div class="line"><a name="l00858"></a><span class="lineno"> 858</span> </div>
|
|
<div class="line"><a name="l00859"></a><span class="lineno"> 859</span>  <span class="comment">// each thread takes care of a subset of lists</span></div>
|
|
<div class="line"><a name="l00860"></a><span class="lineno"> 860</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < n; i++) {</div>
|
|
<div class="line"><a name="l00861"></a><span class="lineno"> 861</span> </div>
|
|
<div class="line"><a name="l00862"></a><span class="lineno"> 862</span>  <span class="keywordtype">long</span> list_no = idx [i];</div>
|
|
<div class="line"><a name="l00863"></a><span class="lineno"> 863</span>  <span class="keywordflow">if</span> (list_no >= 0 && list_no % nt == rank) {</div>
|
|
<div class="line"><a name="l00864"></a><span class="lineno"> 864</span>  <span class="keywordtype">long</span> <span class="keywordtype">id</span> = xids ? xids[i] : ntotal + i;</div>
|
|
<div class="line"><a name="l00865"></a><span class="lineno"> 865</span> </div>
|
|
<div class="line"><a name="l00866"></a><span class="lineno"> 866</span>  assert (list_no < nlist);</div>
|
|
<div class="line"><a name="l00867"></a><span class="lineno"> 867</span> </div>
|
|
<div class="line"><a name="l00868"></a><span class="lineno"> 868</span>  ids[list_no].push_back (<span class="keywordtype">id</span>);</div>
|
|
<div class="line"><a name="l00869"></a><span class="lineno"> 869</span>  nadd++;</div>
|
|
<div class="line"><a name="l00870"></a><span class="lineno"> 870</span>  quantizer->compute_residual (</div>
|
|
<div class="line"><a name="l00871"></a><span class="lineno"> 871</span>  x + i * d, residual.data(), list_no);</div>
|
|
<div class="line"><a name="l00872"></a><span class="lineno"> 872</span> </div>
|
|
<div class="line"><a name="l00873"></a><span class="lineno"> 873</span>  <span class="keywordtype">size_t</span> cur_size = codes[list_no].size();</div>
|
|
<div class="line"><a name="l00874"></a><span class="lineno"> 874</span>  codes[list_no].resize (cur_size + code_size);</div>
|
|
<div class="line"><a name="l00875"></a><span class="lineno"> 875</span> </div>
|
|
<div class="line"><a name="l00876"></a><span class="lineno"> 876</span>  squant->encode_vector (residual.data(),</div>
|
|
<div class="line"><a name="l00877"></a><span class="lineno"> 877</span>  codes[list_no].data() + cur_size);</div>
|
|
<div class="line"><a name="l00878"></a><span class="lineno"> 878</span>  }</div>
|
|
<div class="line"><a name="l00879"></a><span class="lineno"> 879</span>  }</div>
|
|
<div class="line"><a name="l00880"></a><span class="lineno"> 880</span>  }</div>
|
|
<div class="line"><a name="l00881"></a><span class="lineno"> 881</span>  ntotal += nadd;</div>
|
|
<div class="line"><a name="l00882"></a><span class="lineno"> 882</span> }</div>
|
|
<div class="line"><a name="l00883"></a><span class="lineno"> 883</span> </div>
|
|
<div class="line"><a name="l00884"></a><span class="lineno"> 884</span> <span class="keyword">namespace </span>{</div>
|
|
<div class="line"><a name="l00885"></a><span class="lineno"> 885</span> </div>
|
|
<div class="line"><a name="l00886"></a><span class="lineno"> 886</span> <span class="keywordtype">void</span> search_with_probes_ip (<span class="keyword">const</span> <a class="code" href="structfaiss_1_1IndexIVFScalarQuantizer.html">IndexIVFScalarQuantizer</a> & index,</div>
|
|
<div class="line"><a name="l00887"></a><span class="lineno"> 887</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> *x,</div>
|
|
<div class="line"><a name="l00888"></a><span class="lineno"> 888</span>  <span class="keyword">const</span> idx_t *cent_ids, <span class="keyword">const</span> <span class="keywordtype">float</span> *cent_dis,</div>
|
|
<div class="line"><a name="l00889"></a><span class="lineno"> 889</span>  <span class="keyword">const</span> Quantizer & quant,</div>
|
|
<div class="line"><a name="l00890"></a><span class="lineno"> 890</span>  <span class="keywordtype">int</span> k, <span class="keywordtype">float</span> *simi, idx_t *idxi,</div>
|
|
<div class="line"><a name="l00891"></a><span class="lineno"> 891</span>  <span class="keywordtype">bool</span> store_pairs)</div>
|
|
<div class="line"><a name="l00892"></a><span class="lineno"> 892</span> {</div>
|
|
<div class="line"><a name="l00893"></a><span class="lineno"> 893</span>  <span class="keywordtype">int</span> nprobe = index.<a class="code" href="structfaiss_1_1IndexIVF.html#affed235eadf27a13d753ee4d33a1dc58">nprobe</a>;</div>
|
|
<div class="line"><a name="l00894"></a><span class="lineno"> 894</span>  <span class="keywordtype">size_t</span> code_size = index.<a class="code" href="structfaiss_1_1IndexIVF.html#a46d1aeddb60643c5b3f096147c3e028f">code_size</a>;</div>
|
|
<div class="line"><a name="l00895"></a><span class="lineno"> 895</span>  <span class="keywordtype">size_t</span> d = index.<a class="code" href="structfaiss_1_1Index.html#a2a002388d2c081c2dbab8508dcefe73d">d</a>;</div>
|
|
<div class="line"><a name="l00896"></a><span class="lineno"> 896</span>  std::vector<float> decoded(d);</div>
|
|
<div class="line"><a name="l00897"></a><span class="lineno"> 897</span>  minheap_heapify (k, simi, idxi);</div>
|
|
<div class="line"><a name="l00898"></a><span class="lineno"> 898</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < nprobe; i++) {</div>
|
|
<div class="line"><a name="l00899"></a><span class="lineno"> 899</span>  idx_t list_no = cent_ids[i];</div>
|
|
<div class="line"><a name="l00900"></a><span class="lineno"> 900</span>  <span class="keywordflow">if</span> (list_no < 0) <span class="keywordflow">break</span>;</div>
|
|
<div class="line"><a name="l00901"></a><span class="lineno"> 901</span>  <span class="keywordtype">float</span> accu0 = cent_dis[i];</div>
|
|
<div class="line"><a name="l00902"></a><span class="lineno"> 902</span> </div>
|
|
<div class="line"><a name="l00903"></a><span class="lineno"> 903</span>  <span class="keyword">const</span> std::vector<idx_t> & ids = index.<a class="code" href="structfaiss_1_1IndexIVF.html#af16d325f5bef22b2e5f90ceea796e80d">ids</a>[list_no];</div>
|
|
<div class="line"><a name="l00904"></a><span class="lineno"> 904</span>  <span class="keyword">const</span> uint8_t* codes = index.codes[list_no].data();</div>
|
|
<div class="line"><a name="l00905"></a><span class="lineno"> 905</span> </div>
|
|
<div class="line"><a name="l00906"></a><span class="lineno"> 906</span>  SimilarityIP sim(x, accu0);</div>
|
|
<div class="line"><a name="l00907"></a><span class="lineno"> 907</span> </div>
|
|
<div class="line"><a name="l00908"></a><span class="lineno"> 908</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> j = 0; j < ids.size(); j++) {</div>
|
|
<div class="line"><a name="l00909"></a><span class="lineno"> 909</span> </div>
|
|
<div class="line"><a name="l00910"></a><span class="lineno"> 910</span>  <span class="keywordtype">float</span> accu = quant.compute_distance_IP(sim, codes);</div>
|
|
<div class="line"><a name="l00911"></a><span class="lineno"> 911</span> </div>
|
|
<div class="line"><a name="l00912"></a><span class="lineno"> 912</span>  <span class="keywordflow">if</span> (accu > simi [0]) {</div>
|
|
<div class="line"><a name="l00913"></a><span class="lineno"> 913</span>  minheap_pop (k, simi, idxi);</div>
|
|
<div class="line"><a name="l00914"></a><span class="lineno"> 914</span>  <span class="keywordtype">long</span> <span class="keywordtype">id</span> = store_pairs ? (list_no << 32 | j) : ids[j];</div>
|
|
<div class="line"><a name="l00915"></a><span class="lineno"> 915</span>  minheap_push (k, simi, idxi, accu, <span class="keywordtype">id</span>);</div>
|
|
<div class="line"><a name="l00916"></a><span class="lineno"> 916</span>  }</div>
|
|
<div class="line"><a name="l00917"></a><span class="lineno"> 917</span>  codes += code_size;</div>
|
|
<div class="line"><a name="l00918"></a><span class="lineno"> 918</span>  }</div>
|
|
<div class="line"><a name="l00919"></a><span class="lineno"> 919</span> </div>
|
|
<div class="line"><a name="l00920"></a><span class="lineno"> 920</span>  }</div>
|
|
<div class="line"><a name="l00921"></a><span class="lineno"> 921</span>  minheap_reorder (k, simi, idxi);</div>
|
|
<div class="line"><a name="l00922"></a><span class="lineno"> 922</span> }</div>
|
|
<div class="line"><a name="l00923"></a><span class="lineno"> 923</span> </div>
|
|
<div class="line"><a name="l00924"></a><span class="lineno"> 924</span> <span class="keywordtype">void</span> search_with_probes_L2 (<span class="keyword">const</span> IndexIVFScalarQuantizer & index,</div>
|
|
<div class="line"><a name="l00925"></a><span class="lineno"> 925</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> *x_in,</div>
|
|
<div class="line"><a name="l00926"></a><span class="lineno"> 926</span>  <span class="keyword">const</span> idx_t *cent_ids,</div>
|
|
<div class="line"><a name="l00927"></a><span class="lineno"> 927</span>  <span class="keyword">const</span> Index *quantizer,</div>
|
|
<div class="line"><a name="l00928"></a><span class="lineno"> 928</span>  <span class="keyword">const</span> Quantizer & quant,</div>
|
|
<div class="line"><a name="l00929"></a><span class="lineno"> 929</span>  <span class="keywordtype">int</span> k, <span class="keywordtype">float</span> *simi, idx_t *idxi,</div>
|
|
<div class="line"><a name="l00930"></a><span class="lineno"> 930</span>  <span class="keywordtype">bool</span> store_pairs)</div>
|
|
<div class="line"><a name="l00931"></a><span class="lineno"> 931</span> {</div>
|
|
<div class="line"><a name="l00932"></a><span class="lineno"> 932</span>  <span class="keywordtype">int</span> nprobe = index.nprobe;</div>
|
|
<div class="line"><a name="l00933"></a><span class="lineno"> 933</span>  <span class="keywordtype">size_t</span> code_size = index.code_size;</div>
|
|
<div class="line"><a name="l00934"></a><span class="lineno"> 934</span>  <span class="keywordtype">size_t</span> d = index.d;</div>
|
|
<div class="line"><a name="l00935"></a><span class="lineno"> 935</span>  std::vector<float> decoded(d), x(d);</div>
|
|
<div class="line"><a name="l00936"></a><span class="lineno"> 936</span>  maxheap_heapify (k, simi, idxi);</div>
|
|
<div class="line"><a name="l00937"></a><span class="lineno"> 937</span>  <span class="keywordflow">for</span> (<span class="keywordtype">int</span> i = 0; i < nprobe; i++) {</div>
|
|
<div class="line"><a name="l00938"></a><span class="lineno"> 938</span>  idx_t list_no = cent_ids[i];</div>
|
|
<div class="line"><a name="l00939"></a><span class="lineno"> 939</span>  <span class="keywordflow">if</span> (list_no < 0) <span class="keywordflow">break</span>;</div>
|
|
<div class="line"><a name="l00940"></a><span class="lineno"> 940</span> </div>
|
|
<div class="line"><a name="l00941"></a><span class="lineno"> 941</span>  <span class="keyword">const</span> std::vector<idx_t> & ids = index.ids[list_no];</div>
|
|
<div class="line"><a name="l00942"></a><span class="lineno"> 942</span>  <span class="keyword">const</span> uint8_t* codes = index.codes[list_no].data();</div>
|
|
<div class="line"><a name="l00943"></a><span class="lineno"> 943</span> </div>
|
|
<div class="line"><a name="l00944"></a><span class="lineno"> 944</span>  <span class="comment">// shift of x_in wrt centroid</span></div>
|
|
<div class="line"><a name="l00945"></a><span class="lineno"> 945</span>  quantizer->compute_residual (x_in, x.data(), list_no);</div>
|
|
<div class="line"><a name="l00946"></a><span class="lineno"> 946</span> </div>
|
|
<div class="line"><a name="l00947"></a><span class="lineno"> 947</span>  SimilarityL2 sim(x.data());</div>
|
|
<div class="line"><a name="l00948"></a><span class="lineno"> 948</span> </div>
|
|
<div class="line"><a name="l00949"></a><span class="lineno"> 949</span>  <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> j = 0; j < ids.size(); j++) {</div>
|
|
<div class="line"><a name="l00950"></a><span class="lineno"> 950</span> </div>
|
|
<div class="line"><a name="l00951"></a><span class="lineno"> 951</span>  <span class="keywordtype">float</span> dis = quant.compute_distance_L2 (sim, codes);</div>
|
|
<div class="line"><a name="l00952"></a><span class="lineno"> 952</span> </div>
|
|
<div class="line"><a name="l00953"></a><span class="lineno"> 953</span>  <span class="keywordflow">if</span> (dis < simi [0]) {</div>
|
|
<div class="line"><a name="l00954"></a><span class="lineno"> 954</span>  maxheap_pop (k, simi, idxi);</div>
|
|
<div class="line"><a name="l00955"></a><span class="lineno"> 955</span>  <span class="keywordtype">long</span> <span class="keywordtype">id</span> = store_pairs ? (list_no << 32 | j) : ids[j];</div>
|
|
<div class="line"><a name="l00956"></a><span class="lineno"> 956</span>  maxheap_push (k, simi, idxi, dis, <span class="keywordtype">id</span>);</div>
|
|
<div class="line"><a name="l00957"></a><span class="lineno"> 957</span>  }</div>
|
|
<div class="line"><a name="l00958"></a><span class="lineno"> 958</span>  codes += code_size;</div>
|
|
<div class="line"><a name="l00959"></a><span class="lineno"> 959</span>  }</div>
|
|
<div class="line"><a name="l00960"></a><span class="lineno"> 960</span>  }</div>
|
|
<div class="line"><a name="l00961"></a><span class="lineno"> 961</span>  maxheap_reorder (k, simi, idxi);</div>
|
|
<div class="line"><a name="l00962"></a><span class="lineno"> 962</span> }</div>
|
|
<div class="line"><a name="l00963"></a><span class="lineno"> 963</span> </div>
|
|
<div class="line"><a name="l00964"></a><span class="lineno"> 964</span> } <span class="comment">// anonymous namespace</span></div>
|
|
<div class="line"><a name="l00965"></a><span class="lineno"> 965</span> </div>
|
|
<div class="line"><a name="l00966"></a><span class="lineno"><a class="line" href="structfaiss_1_1IndexIVFScalarQuantizer.html#a341e473a62adcb03e07e53f67c1a7358"> 966</a></span> <span class="keywordtype">void</span> <a class="code" href="structfaiss_1_1IndexIVFScalarQuantizer.html#a341e473a62adcb03e07e53f67c1a7358">IndexIVFScalarQuantizer::search_preassigned</a> (</div>
|
|
<div class="line"><a name="l00967"></a><span class="lineno"> 967</span>  idx_t n, <span class="keyword">const</span> <span class="keywordtype">float</span> *x, idx_t k,</div>
|
|
<div class="line"><a name="l00968"></a><span class="lineno"> 968</span>  <span class="keyword">const</span> idx_t *idx,</div>
|
|
<div class="line"><a name="l00969"></a><span class="lineno"> 969</span>  <span class="keyword">const</span> <span class="keywordtype">float</span> *dis,</div>
|
|
<div class="line"><a name="l00970"></a><span class="lineno"> 970</span>  <span class="keywordtype">float</span> *distances, idx_t *labels,</div>
|
|
<div class="line"><a name="l00971"></a><span class="lineno"> 971</span>  <span class="keywordtype">bool</span> store_pairs)<span class="keyword"> const</span></div>
|
|
<div class="line"><a name="l00972"></a><span class="lineno"> 972</span> <span class="keyword"></span>{</div>
|
|
<div class="line"><a name="l00973"></a><span class="lineno"> 973</span>  FAISS_THROW_IF_NOT (<a class="code" href="structfaiss_1_1Index.html#a6e92732617c4dbe364e7678dd8773a7f">is_trained</a>);</div>
|
|
<div class="line"><a name="l00974"></a><span class="lineno"> 974</span> </div>
|
|
<div class="line"><a name="l00975"></a><span class="lineno"> 975</span>  Quantizer *squant = select_quantizer (sq);</div>
|
|
<div class="line"><a name="l00976"></a><span class="lineno"> 976</span>  <a class="code" href="structfaiss_1_1ScopeDeleter1.html">ScopeDeleter1<Quantizer></a> del(squant);</div>
|
|
<div class="line"><a name="l00977"></a><span class="lineno"> 977</span> </div>
|
|
<div class="line"><a name="l00978"></a><span class="lineno"> 978</span>  <span class="keywordflow">if</span> (<a class="code" href="structfaiss_1_1Index.html#a8e18f641854b2bde83ecff0a2f9a6f4e">metric_type</a> == METRIC_INNER_PRODUCT) {</div>
|
|
<div class="line"><a name="l00979"></a><span class="lineno"> 979</span> <span class="preprocessor">#pragma omp parallel for</span></div>
|
|
<div class="line"><a name="l00980"></a><span class="lineno"> 980</span> <span class="preprocessor"></span> <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < n; i++) {</div>
|
|
<div class="line"><a name="l00981"></a><span class="lineno"> 981</span>  search_with_probes_ip (*<span class="keyword">this</span>, x + i * d,</div>
|
|
<div class="line"><a name="l00982"></a><span class="lineno"> 982</span>  idx + i * nprobe, dis + i * nprobe, *squant,</div>
|
|
<div class="line"><a name="l00983"></a><span class="lineno"> 983</span>  k, distances + i * k, labels + i * k,</div>
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<div class="line"><a name="l00984"></a><span class="lineno"> 984</span>  store_pairs);</div>
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<div class="line"><a name="l00985"></a><span class="lineno"> 985</span>  }</div>
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<div class="line"><a name="l00986"></a><span class="lineno"> 986</span>  } <span class="keywordflow">else</span> {</div>
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<div class="line"><a name="l00987"></a><span class="lineno"> 987</span> <span class="preprocessor">#pragma omp parallel for</span></div>
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<div class="line"><a name="l00988"></a><span class="lineno"> 988</span> <span class="preprocessor"></span> <span class="keywordflow">for</span> (<span class="keywordtype">size_t</span> i = 0; i < n; i++) {</div>
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<div class="line"><a name="l00989"></a><span class="lineno"> 989</span>  search_with_probes_L2 (*<span class="keyword">this</span>, x + i * d,</div>
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<div class="line"><a name="l00990"></a><span class="lineno"> 990</span>  idx + i * nprobe, quantizer, *squant,</div>
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<div class="line"><a name="l00991"></a><span class="lineno"> 991</span>  k, distances + i * k, labels + i * k,</div>
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<div class="line"><a name="l00992"></a><span class="lineno"> 992</span>  store_pairs);</div>
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<div class="line"><a name="l00993"></a><span class="lineno"> 993</span>  }</div>
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<div class="line"><a name="l00994"></a><span class="lineno"> 994</span>  }</div>
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<div class="line"><a name="l00995"></a><span class="lineno"> 995</span> </div>
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<div class="line"><a name="l00996"></a><span class="lineno"> 996</span> }</div>
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<div class="line"><a name="l00997"></a><span class="lineno"> 997</span> </div>
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<div class="line"><a name="l00998"></a><span class="lineno"> 998</span> </div>
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<div class="line"><a name="l00999"></a><span class="lineno"> 999</span> }</div>
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<div class="ttc" id="structfaiss_1_1IndexIVF_html"><div class="ttname"><a href="structfaiss_1_1IndexIVF.html">faiss::IndexIVF</a></div><div class="ttdef"><b>Definition:</b> <a href="IndexIVF_8h_source.html#l00045">IndexIVF.h:45</a></div></div>
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<div class="ttc" id="structfaiss_1_1ScalarQuantizer_html_a647b8774e4cd8ca5623a194f5c7f8a33"><div class="ttname"><a href="structfaiss_1_1ScalarQuantizer.html#a647b8774e4cd8ca5623a194f5c7f8a33">faiss::ScalarQuantizer::code_size</a></div><div class="ttdeci">size_t code_size</div><div class="ttdoc">bytes per vector </div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8h_source.html#l00060">IndexScalarQuantizer.h:60</a></div></div>
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<div class="ttc" id="structfaiss_1_1ScalarQuantizer_html_a1201dbd1611fa5c10782ade5d0e4952e"><div class="ttname"><a href="structfaiss_1_1ScalarQuantizer.html#a1201dbd1611fa5c10782ade5d0e4952e">faiss::ScalarQuantizer::QuantizerType</a></div><div class="ttdeci">QuantizerType</div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8h_source.html#l00032">IndexScalarQuantizer.h:32</a></div></div>
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<div class="ttc" id="structfaiss_1_1IndexScalarQuantizer_html_abf24732c29106bb808148c3d30599662"><div class="ttname"><a href="structfaiss_1_1IndexScalarQuantizer.html#abf24732c29106bb808148c3d30599662">faiss::IndexScalarQuantizer::search</a></div><div class="ttdeci">void search(idx_t n, const float *x, idx_t k, float *distances, idx_t *labels) const override</div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8cpp_source.html#l00727">IndexScalarQuantizer.cpp:727</a></div></div>
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<div class="ttc" id="structfaiss_1_1IndexIVFScalarQuantizer_html_ac05d7fbfed59c85d1cf8ae526d279744"><div class="ttname"><a href="structfaiss_1_1IndexIVFScalarQuantizer.html#ac05d7fbfed59c85d1cf8ae526d279744">faiss::IndexIVFScalarQuantizer::train_residual</a></div><div class="ttdeci">void train_residual(idx_t n, const float *x) override</div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8cpp_source.html#l00824">IndexScalarQuantizer.cpp:824</a></div></div>
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<div class="ttc" id="structfaiss_1_1ScalarQuantizer_html_a867ad0000e4ccfd40bbb1e01e7882d06ab0709ff74c1b882b64a7fdd7ca5df9a3"><div class="ttname"><a href="structfaiss_1_1ScalarQuantizer.html#a867ad0000e4ccfd40bbb1e01e7882d06ab0709ff74c1b882b64a7fdd7ca5df9a3">faiss::ScalarQuantizer::RS_optim</a></div><div class="ttdoc">alternate optimization of reconstruction error </div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8h_source.html#l00050">IndexScalarQuantizer.h:50</a></div></div>
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<div class="ttc" id="structfaiss_1_1IndexScalarQuantizer_html"><div class="ttname"><a href="structfaiss_1_1IndexScalarQuantizer.html">faiss::IndexScalarQuantizer</a></div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8h_source.html#l00082">IndexScalarQuantizer.h:82</a></div></div>
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<div class="ttc" id="structfaiss_1_1ScalarQuantizer_html_a1201dbd1611fa5c10782ade5d0e4952ea029f07a15ea64e7e73daaf9633ac429a"><div class="ttname"><a href="structfaiss_1_1ScalarQuantizer.html#a1201dbd1611fa5c10782ade5d0e4952ea029f07a15ea64e7e73daaf9633ac429a">faiss::ScalarQuantizer::QT_8bit_uniform</a></div><div class="ttdoc">same, shared range for all dimensions </div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8h_source.html#l00035">IndexScalarQuantizer.h:35</a></div></div>
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<div class="ttc" id="structfaiss_1_1IndexScalarQuantizer_html_ad49602f9ecfcaa2ec8737a449b69ccd7"><div class="ttname"><a href="structfaiss_1_1IndexScalarQuantizer.html#ad49602f9ecfcaa2ec8737a449b69ccd7">faiss::IndexScalarQuantizer::add</a></div><div class="ttdeci">void add(idx_t n, const float *x) override</div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8cpp_source.html#l00719">IndexScalarQuantizer.cpp:719</a></div></div>
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<div class="ttc" id="structfaiss_1_1IndexIVF_html_affed235eadf27a13d753ee4d33a1dc58"><div class="ttname"><a href="structfaiss_1_1IndexIVF.html#affed235eadf27a13d753ee4d33a1dc58">faiss::IndexIVF::nprobe</a></div><div class="ttdeci">size_t nprobe</div><div class="ttdoc">number of probes at query time </div><div class="ttdef"><b>Definition:</b> <a href="IndexIVF_8h_source.html#l00047">IndexIVF.h:47</a></div></div>
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<div class="ttc" id="structfaiss_1_1ScalarQuantizer_html_a1201dbd1611fa5c10782ade5d0e4952eacd3d1bd71533a7bc52149e4b3d1db13b"><div class="ttname"><a href="structfaiss_1_1ScalarQuantizer.html#a1201dbd1611fa5c10782ade5d0e4952eacd3d1bd71533a7bc52149e4b3d1db13b">faiss::ScalarQuantizer::QT_4bit</a></div><div class="ttdoc">4 bits per component </div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8h_source.html#l00034">IndexScalarQuantizer.h:34</a></div></div>
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<div class="ttc" id="structfaiss_1_1Index_html_a8bc5d8d1cd0dd7b34b3c98a9f76b4a9c"><div class="ttname"><a href="structfaiss_1_1Index.html#a8bc5d8d1cd0dd7b34b3c98a9f76b4a9c">faiss::Index::assign</a></div><div class="ttdeci">void assign(idx_t n, const float *x, idx_t *labels, idx_t k=1)</div><div class="ttdef"><b>Definition:</b> <a href="Index_8cpp_source.html#l00023">Index.cpp:23</a></div></div>
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<div class="ttc" id="structfaiss_1_1IndexScalarQuantizer_html_af0d6b901a2a02fff34e5c7c1ea5b8d55"><div class="ttname"><a href="structfaiss_1_1IndexScalarQuantizer.html#af0d6b901a2a02fff34e5c7c1ea5b8d55">faiss::IndexScalarQuantizer::reset</a></div><div class="ttdeci">void reset() override</div><div class="ttdoc">removes all elements from the database. </div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8cpp_source.html#l00784">IndexScalarQuantizer.cpp:784</a></div></div>
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<div class="ttc" id="structfaiss_1_1ScopeDeleter1_html"><div class="ttname"><a href="structfaiss_1_1ScopeDeleter1.html">faiss::ScopeDeleter1</a></div><div class="ttdef"><b>Definition:</b> <a href="FaissException_8h_source.html#l00052">FaissException.h:52</a></div></div>
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<div class="ttc" id="structfaiss_1_1ScopeDeleter_html"><div class="ttname"><a href="structfaiss_1_1ScopeDeleter.html">faiss::ScopeDeleter</a></div><div class="ttdef"><b>Definition:</b> <a href="FaissException_8h_source.html#l00039">FaissException.h:39</a></div></div>
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<div class="ttc" id="structfaiss_1_1ScalarQuantizer_html"><div class="ttname"><a href="structfaiss_1_1ScalarQuantizer.html">faiss::ScalarQuantizer</a></div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8h_source.html#l00030">IndexScalarQuantizer.h:30</a></div></div>
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<div class="ttc" id="structfaiss_1_1IndexIVF_html_af16d325f5bef22b2e5f90ceea796e80d"><div class="ttname"><a href="structfaiss_1_1IndexIVF.html#af16d325f5bef22b2e5f90ceea796e80d">faiss::IndexIVF::ids</a></div><div class="ttdeci">std::vector< std::vector< long > > ids</div><div class="ttdoc">Inverted lists for indexes. </div><div class="ttdef"><b>Definition:</b> <a href="IndexIVF_8h_source.html#l00062">IndexIVF.h:62</a></div></div>
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<div class="ttc" id="structfaiss_1_1IndexIVFScalarQuantizer_html_afa95c17787b7e3dbed9309b440d4d748"><div class="ttname"><a href="structfaiss_1_1IndexIVFScalarQuantizer.html#afa95c17787b7e3dbed9309b440d4d748">faiss::IndexIVFScalarQuantizer::add_with_ids</a></div><div class="ttdeci">void add_with_ids(idx_t n, const float *x, const long *xids) override</div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8cpp_source.html#l00843">IndexScalarQuantizer.cpp:843</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_1IndexIVF_html_a4b40cc7a70dff41196a3b8769586667a"><div class="ttname"><a href="structfaiss_1_1IndexIVF.html#a4b40cc7a70dff41196a3b8769586667a">faiss::IndexIVF::quantizer</a></div><div class="ttdeci">Index * quantizer</div><div class="ttdoc">quantizer that maps vectors to inverted lists </div><div class="ttdef"><b>Definition:</b> <a href="IndexIVF_8h_source.html#l00049">IndexIVF.h:49</a></div></div>
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<div class="ttc" id="structfaiss_1_1IndexScalarQuantizer_html_a861fa059f9d4ced9147e08193a2be9be"><div class="ttname"><a href="structfaiss_1_1IndexScalarQuantizer.html#a861fa059f9d4ced9147e08193a2be9be">faiss::IndexScalarQuantizer::codes</a></div><div class="ttdeci">std::vector< uint8_t > codes</div><div class="ttdoc">Codes. Size ntotal * pq.code_size. </div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8h_source.html#l00087">IndexScalarQuantizer.h:87</a></div></div>
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<div class="ttc" id="structfaiss_1_1IndexScalarQuantizer_html_a71381f74754d8a54812e80af46a2a83a"><div class="ttname"><a href="structfaiss_1_1IndexScalarQuantizer.html#a71381f74754d8a54812e80af46a2a83a">faiss::IndexScalarQuantizer::sq</a></div><div class="ttdeci">ScalarQuantizer sq</div><div class="ttdoc">Used to encode the vectors. </div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8h_source.html#l00084">IndexScalarQuantizer.h:84</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="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="structfaiss_1_1ScalarQuantizer_html_a867ad0000e4ccfd40bbb1e01e7882d06"><div class="ttname"><a href="structfaiss_1_1ScalarQuantizer.html#a867ad0000e4ccfd40bbb1e01e7882d06">faiss::ScalarQuantizer::RangeStat</a></div><div class="ttdeci">RangeStat</div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8h_source.html#l00046">IndexScalarQuantizer.h:46</a></div></div>
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<div class="ttc" id="structfaiss_1_1IndexIVFScalarQuantizer_html"><div class="ttname"><a href="structfaiss_1_1IndexIVFScalarQuantizer.html">faiss::IndexIVFScalarQuantizer</a></div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8h_source.html#l00129">IndexScalarQuantizer.h:129</a></div></div>
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<div class="ttc" id="structfaiss_1_1ScalarQuantizer_html_a867ad0000e4ccfd40bbb1e01e7882d06ae41cccec3a7acbcb3a47fa63c2bfb4c8"><div class="ttname"><a href="structfaiss_1_1ScalarQuantizer.html#a867ad0000e4ccfd40bbb1e01e7882d06ae41cccec3a7acbcb3a47fa63c2bfb4c8">faiss::ScalarQuantizer::RS_quantiles</a></div><div class="ttdoc">[Q(rs), Q(1-rs)] </div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8h_source.html#l00049">IndexScalarQuantizer.h:49</a></div></div>
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<div class="ttc" id="structfaiss_1_1IndexIVFScalarQuantizer_html_a341e473a62adcb03e07e53f67c1a7358"><div class="ttname"><a href="structfaiss_1_1IndexIVFScalarQuantizer.html#a341e473a62adcb03e07e53f67c1a7358">faiss::IndexIVFScalarQuantizer::search_preassigned</a></div><div class="ttdeci">void search_preassigned(idx_t n, const float *x, idx_t k, const idx_t *assign, const float *centroid_dis, float *distances, idx_t *labels, bool store_pairs) const override</div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8cpp_source.html#l00966">IndexScalarQuantizer.cpp:966</a></div></div>
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<div class="ttc" id="structfaiss_1_1ScalarQuantizer_html_a867ad0000e4ccfd40bbb1e01e7882d06afb4b9f4ee9003fa0193e6de69632f7a0"><div class="ttname"><a href="structfaiss_1_1ScalarQuantizer.html#a867ad0000e4ccfd40bbb1e01e7882d06afb4b9f4ee9003fa0193e6de69632f7a0">faiss::ScalarQuantizer::RS_meanstd</a></div><div class="ttdoc">[mean - std * rs, mean + std * rs] </div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8h_source.html#l00048">IndexScalarQuantizer.h:48</a></div></div>
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<div class="ttc" id="structfaiss_1_1ScalarQuantizer_html_a7ab9e9158da1777d45e6f9bf73bfd489"><div class="ttname"><a href="structfaiss_1_1ScalarQuantizer.html#a7ab9e9158da1777d45e6f9bf73bfd489">faiss::ScalarQuantizer::decode</a></div><div class="ttdeci">void decode(const uint8_t *code, float *x, size_t n) const </div><div class="ttdoc">decode a vector from a given code (or n vectors if third argument) </div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8cpp_source.html#l00685">IndexScalarQuantizer.cpp:685</a></div></div>
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<div class="ttc" id="structfaiss_1_1ScalarQuantizer_html_a2bccf276565c4f80fed3d0c715c58816"><div class="ttname"><a href="structfaiss_1_1ScalarQuantizer.html#a2bccf276565c4f80fed3d0c715c58816">faiss::ScalarQuantizer::compute_codes</a></div><div class="ttdeci">void compute_codes(const float *x, uint8_t *codes, size_t n) const </div><div class="ttdoc">same as compute_code for several vectors </div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8cpp_source.html#l00674">IndexScalarQuantizer.cpp:674</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="structfaiss_1_1ScalarQuantizer_html_a1201dbd1611fa5c10782ade5d0e4952ea1650389e3efa052ff60177d502328a2c"><div class="ttname"><a href="structfaiss_1_1ScalarQuantizer.html#a1201dbd1611fa5c10782ade5d0e4952ea1650389e3efa052ff60177d502328a2c">faiss::ScalarQuantizer::QT_8bit</a></div><div class="ttdoc">8 bits per component </div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8h_source.html#l00033">IndexScalarQuantizer.h:33</a></div></div>
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<div class="ttc" id="structfaiss_1_1Index_html"><div class="ttname"><a href="structfaiss_1_1Index.html">faiss::Index</a></div><div class="ttdef"><b>Definition:</b> <a href="Index_8h_source.html#l00060">Index.h:60</a></div></div>
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<div class="ttc" id="structfaiss_1_1IndexScalarQuantizer_html_a06e6935b75f0b209f65fffa1c9e1477c"><div class="ttname"><a href="structfaiss_1_1IndexScalarQuantizer.html#a06e6935b75f0b209f65fffa1c9e1477c">faiss::IndexScalarQuantizer::reconstruct_n</a></div><div class="ttdeci">void reconstruct_n(idx_t i0, idx_t ni, float *recons) const override</div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8cpp_source.html#l00790">IndexScalarQuantizer.cpp:790</a></div></div>
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<div class="ttc" id="structfaiss_1_1IndexScalarQuantizer_html_a8fb8680f64465d643d96119da58099f3"><div class="ttname"><a href="structfaiss_1_1IndexScalarQuantizer.html#a8fb8680f64465d643d96119da58099f3">faiss::IndexScalarQuantizer::reconstruct</a></div><div class="ttdeci">void reconstruct(idx_t key, float *recons) const override</div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8cpp_source.html#l00800">IndexScalarQuantizer.cpp:800</a></div></div>
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<div class="ttc" id="structfaiss_1_1ScalarQuantizer_html_a867ad0000e4ccfd40bbb1e01e7882d06aa52f2f14616c61c04baf6323d43588fd"><div class="ttname"><a href="structfaiss_1_1ScalarQuantizer.html#a867ad0000e4ccfd40bbb1e01e7882d06aa52f2f14616c61c04baf6323d43588fd">faiss::ScalarQuantizer::RS_minmax</a></div><div class="ttdoc">[min - rs*(max-min), max + rs*(max-min)] </div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8h_source.html#l00047">IndexScalarQuantizer.h:47</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="structfaiss_1_1Index_html_aaae77608bbda70b1098897e9167a82f9"><div class="ttname"><a href="structfaiss_1_1Index.html#aaae77608bbda70b1098897e9167a82f9">faiss::Index::compute_residual</a></div><div class="ttdeci">void compute_residual(const float *x, float *residual, idx_t key) const </div><div class="ttdef"><b>Definition:</b> <a href="Index_8cpp_source.html#l00056">Index.cpp:56</a></div></div>
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<div class="ttc" id="structfaiss_1_1IndexScalarQuantizer_html_a300647e9cdac9acd160f2c55c610056b"><div class="ttname"><a href="structfaiss_1_1IndexScalarQuantizer.html#a300647e9cdac9acd160f2c55c610056b">faiss::IndexScalarQuantizer::train</a></div><div class="ttdeci">void train(idx_t n, const float *x) override</div><div class="ttdef"><b>Definition:</b> <a href="IndexScalarQuantizer_8cpp_source.html#l00713">IndexScalarQuantizer.cpp:713</a></div></div>
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<div class="ttc" id="structfaiss_1_1IndexIVF_html_a46d1aeddb60643c5b3f096147c3e028f"><div class="ttname"><a href="structfaiss_1_1IndexIVF.html#a46d1aeddb60643c5b3f096147c3e028f">faiss::IndexIVF::code_size</a></div><div class="ttdeci">size_t code_size</div><div class="ttdoc">code size per vector in bytes </div><div class="ttdef"><b>Definition:</b> <a href="IndexIVF_8h_source.html#l00064">IndexIVF.h:64</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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