开发环境 centos7 64位
1.安装Anaconda
wget https://mirrors.tuna.tsinghua.edu.cn/anaconda/archive/Anaconda2-4.3.0-Linux-x86_64.sh
# 修改权限
chmod +x Anaconda2-4.3.0-Linux-x86_64.sh
# 执行默认安装,一路Enter键。
bash Anaconda2-4.3.0-Linux-x86_64.sh
# 检测1
conda list
出现 N多Python依赖包
# 检测2
python --version
出现带Anaconda标记的Python,如下:
Python 2.7.13 :: Anaconda custom (64-bit)
2.更新 conda
conda update conda
3.安装mkl
conda install mkl
4.安装faiss-cpu
conda install faiss-cpu -c pytorch
5.测试是否安装成功
python -c "import faiss"
6.官方demo
import numpy as np
import faiss # make faiss available
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.
index = faiss.IndexFlatL2(d) # build the index
print(index.is_trained)
index.add(xb) # add vectors to the index
print(index.ntotal)
k = 4 # we want to see 4 nearest neighbors
D, I = index.search(xq, k) # actual search
print(I[:5]) # neighbors of the 5 first queries
print(D[-5:]) # neighbors of the 5 last queries
相关网站:https://blog.csdn.net/kanbuqinghuanyizhang/article/details/80774609