# Copyright (c) 2015-present, Facebook, Inc.
# All rights reserved.
#
# This source code is licensed under the BSD+Patents license found in the
# LICENSE file in the root directory of this source tree.
import numpy as np
d = 64 # dimension
nb = 100000 # database size
nq = 10000 # nb of queries
np.random.seed(1234) # make reproducible
xb = np.random.random((nb, d)).astype('float32')
xb[:, 0] += np.arange(nb) / 1000.
xq = np.random.random((nq, d)).astype('float32')
xq[:, 0] += np.arange(nq) / 1000.
import faiss
nlist = 100
k = 4
quantizer = faiss.IndexFlatL2(d) # the other index
index = faiss.IndexIVFFlat(quantizer, d, nlist, faiss.METRIC_L2)
# here we specify METRIC_L2, by default it performs inner-product search
assert not index.is_trained
index.train(xb)
assert index.is_trained
index.add(xb) # add may be a bit slower as well
D, I = index.search(xq, k) # actual search
print(I[-5:]) # neighbors of the 5 last queries
index.nprobe = 10 # default nprobe is 1, try a few more
D, I = index.search(xq, k)
print(I[-5:]) # neighbors of the 5 last queries-
Lucas Hosseini authored
* Remove transitional print import. * Add example for multiple GPUs in python. * Add example on GPU in C++. * Add example on multiple GPUs in C++. * Add IVFFlat example on GPU in python. * Add Makefile for C++ tutorial examples. * Add IVF index on GPU example in C++.
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