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demo_ondisk_ivf.py
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#!/usr/bin/env python3
# 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 sys
import numpy as np
import faiss
from faiss.contrib.ondisk import merge_ondisk
#################################################################
# Small I/O functions
#################################################################
def ivecs_read(fname):
a = np.fromfile(fname, dtype='int32')
d = a[0]
return a.reshape(-1, d + 1)[:, 1:].copy()
def fvecs_read(fname):
return ivecs_read(fname).view('float32')
#################################################################
# Main program
#################################################################
stage = int(sys.argv[1])
tmpdir = '/tmp/'
if stage == 0:
# train the index
xt = fvecs_read("sift1M/sift_learn.fvecs")
index = faiss.index_factory(xt.shape[1], "IVF4096,Flat")
print("training index")
index.train(xt)
print("write " + tmpdir + "trained.index")
faiss.write_index(index, tmpdir + "trained.index")
if 1 <= stage <= 4:
# add 1/4 of the database to 4 independent indexes
bno = stage - 1
xb = fvecs_read("sift1M/sift_base.fvecs")
i0, i1 = int(bno * xb.shape[0] / 4), int((bno + 1) * xb.shape[0] / 4)
index = faiss.read_index(tmpdir + "trained.index")
print("adding vectors %d:%d" % (i0, i1))
index.add_with_ids(xb[i0:i1], np.arange(i0, i1))
print("write " + tmpdir + "block_%d.index" % bno)
faiss.write_index(index, tmpdir + "block_%d.index" % bno)
if stage == 5:
print('loading trained index')
# construct the output index
index = faiss.read_index(tmpdir + "trained.index")
block_fnames = [
tmpdir + "block_%d.index" % bno
for bno in range(4)
]
merge_ondisk(index, block_fnames, tmpdir + "merged_index.ivfdata")
print("write " + tmpdir + "populated.index")
faiss.write_index(index, tmpdir + "populated.index")
if stage == 6:
# perform a search from disk
print("read " + tmpdir + "populated.index")
index = faiss.read_index(tmpdir + "populated.index")
index.nprobe = 16
# load query vectors and ground-truth
xq = fvecs_read("sift1M/sift_query.fvecs")
gt = ivecs_read("sift1M/sift_groundtruth.ivecs")
D, I = index.search(xq, 5)
recall_at_1 = (I[:, :1] == gt[:, :1]).sum() / float(xq.shape[0])
print("recall@1: %.3f" % recall_at_1)