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How to find the smallest euclidean distance in the database?
We have one array:
[-0.14760402 0.18719167 0.04150053 -0.0921068 -0.16887078 0.02324709
-0.04641612 -0.11630221 0.12370145 -0.07014455 0.24573359 0.03904079
-0.27129778 0.02959204 -0.07295675 0.13609795 -0.13187698 -0.08968797
-0.2012838 -0.16615982 0.0217059 0.00041627 -0.01858913 0.04955338
-0.19024704 -0.18434721 -0.06982315 -0.05426939 0.15494351 -0.10451394
-0.04299729 -0.07180098 -0.1690695 -0.08467829 -0.02749946 -0.00308757
-0.01261706 -0.14929104 0.19307789 -0.05911519 -0.11811744 -0.00415748
0.11933747 0.22268862 0.15321049 -0.04101308 0.12349229 -0.06126648
0.09076166 -0.18876649 0.06199023 0.07674868 0.09749875 0.0716019
0.12201017 -0.19290529 -0.01353829 0.21687341 -0.11010585 0.12630889
0.04276971 0.00293659 -0.10534084 -0.08965943 0.12599346 0.09744062
-0.07307861 -0.21842727 0.18325034 -0.15839542 -0.05597069 0.09004606
-0.089193 -0.11996002 -0.3178705 0.05085036 0.38763958 0.19086862
-0.14595589 0.02082828 -0.01978934 -0.07487711 0.05899249 -0.01674179
-0.11979252 -0.02747795 -0.08680353 0.08834615 0.25229415 0.01445329
0.00105722 0.23681179 0.08904405 -0.09763616 0.01047772 0.13714562
-0.15587574 -0.02978589 -0.03372395 0.0463781 0.15200463 -0.13603318
0.02152741 0.10868748 -0.1757534 0.06744438 -0.0318573 0.01892542
-0.0262807 0.04844372 -0.15358914 -0.05309738 0.22137821 -0.20882189
0.1269407 0.24391431 -0.02090507 0.02553483 0.11997325 0.03864738
0.07777584 0.04860133 -0.09686276 -0.13455498 0.01073158 -0.15386821
0.02141182 0.0842296 ]
[-0.18303205 0.07142412 0.01505323 -0.14673074 -0.17361142 0.02646742
-0.03395279 -0.06831738 0.08645248 -0.07506754 0.22879875 0.00961941
-0.21720028 -0.10564265 0.09235184 0.12250473 -0.09408396 -0.07704318
-0.17983794 -0.10640886 -0.00760378 0.05881869 0.00609878 0.05506223
-0.17767537 -0.30160218 -0.03009136 0.00688204 -0.02562195 -0.02175772
-0.05757777 0.13162929 -0.16575503 -0.06576031 0.01825872 0.09892717
-0.0990886 -0.04563086 0.16782466 0.00385343 -0.1655371 0.02370039
0.06626146 0.26851994 0.25856623 -0.0427581 0.02065502 -0.03230648
0.16015874 -0.30130655 0.06620336 0.1480027 0.08171275 0.02545679
0.0743178 -0.09076802 0.00253361 0.18856071 -0.1644216 -0.03282868
-0.00277766 -0.10307762 -0.12198099 -0.19316623 0.18896221 0.17105345
-0.14985694 -0.1295868 0.08943356 -0.06235509 -0.10340865 0.04370517
-0.19336724 -0.18820783 -0.37302011 0.09345791 0.33356905 0.1724074
-0.21920988 0.01767435 -0.02863912 -0.01240025 0.08466867 0.0631162
-0.08921493 -0.05865925 -0.02537591 0.08397133 0.18167101 -0.01622136
-0.05787662 0.27105331 0.12237041 0.04605677 0.03525903 0.05793242
-0.03242231 -0.06490842 -0.16594143 0.0506063 0.07158192 -0.08893429
0.03126835 0.12600896 -0.18564469 0.23052448 0.03958503 0.06578501
0.01276818 -0.08363014 -0.08138505 -0.0220259 0.09097432 -0.2337397
0.10124329 0.1670257 0.05445097 0.14788289 0.12662688 -0.00762837
-0.00578771 0.04282037 -0.15355538 -0.03583786 0.16012162 -0.03436102
0.05533902 0.09013008]
dist = 1 - numpy.linalg.norm(a - b)
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In monge, this cannot be implemented without comparing the vector with each entry in the database.
To search by vectors, for example , faiss is used
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