Created
August 17, 2017 09:41
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#! /usr/bin/env python2 | |
import numpy as np | |
import faiss | |
import time | |
xd = 100 | |
yd = 1000000 | |
np.random.seed(1234) | |
faiss.omp_set_num_threads(1) | |
print 'xd=%d yd=%d' % (xd, yd) | |
for d in 3, 4, 12, 36, 64: | |
x = faiss.rand(xd * d).reshape(xd, d) | |
y = faiss.rand(yd * d).reshape(yd, d) | |
distances = np.empty((xd, yd), dtype='float32') | |
t0 = time.time() | |
for i in xrange(xd): | |
faiss.fvec_inner_products_ny(faiss.swig_ptr(distances[i]), | |
faiss.swig_ptr(x[i]), | |
faiss.swig_ptr(y), | |
d, yd) | |
t1 = time.time() | |
# sparse verification | |
ntry = 100 | |
num, denom = 0, 0 | |
for t in range(ntry): | |
xi = np.random.randint(xd) | |
yi = np.random.randint(yd) | |
num += abs(distances[xi, yi] - np.dot(x[xi], y[yi])) | |
denom += abs(distances[xi, yi]) | |
print 'd=%d t=%.3f s diff=%g' % (d, t1 - t0, num / denom) |
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