torch序列化 pickle 慢

100张图片 反序列化需要1s，300张需要3s

#coding=utf-8
import time
import numpy as np
import redis
import cv2 as cv
import pickle

import torch

pool = redis.ConnectionPool(host='localhost', port=6379, db=0)
r = redis.StrictRedis(connection_pool=pool)

x = torch.rand(1, 3, 352, 352)

for i in range(3):
    r.set(i,pickle.dumps(x))

start = time.time()
for i in range(100):
    b = r.get(1)
    b=pickle.loads(b)
    # print(b.type)

print('time',time.time()-start)
#
# for i in range(100):
#     data = np.arange(1000 * 4000, dtype='float').reshape(1000, 4000)
#     t1=time.time()
#     r.set(b'list'+str(i),data)
#     print('存入时间',time.time()-t1)
#
# for i in range(100):
#     t2=time.time()
#     list2=r.get

文章来源: blog.csdn.net，作者：网奇，版权归原作者所有，如需转载，请联系作者。

原文链接：blog.csdn.net/jacke121/article/details/85224465