mirror of
https://github.com/facebookresearch/faiss.git
synced 2025-06-03 21:54:02 +08:00
eff0898a13
Summary: Pull Request resolved: https://github.com/facebookresearch/faiss/pull/3966 This actually enables the linting. Manual changes: - tools/arcanist/lint/fbsource-licenselint-config.toml - tools/arcanist/lint/fbsource-lint-engine.toml Automated changes: `arc lint --apply-patches --take LICENSELINT --paths-cmd 'hg files faiss'` Reviewed By: asadoughi Differential Revision: D64484165 fbshipit-source-id: 4f2f6e953c94ef6ebfea8a5ae035ccfbea65ed04
35 lines
1.2 KiB
Python
35 lines
1.2 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
|
|
#
|
|
# This source code is licensed under the MIT 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
|