同步操作将从 PaddlePaddle/Serving 强制同步,此操作会覆盖自 Fork 仓库以来所做的任何修改,且无法恢复!!!
确定后同步将在后台操作,完成时将刷新页面,请耐心等待。
(简体中文|English)
Paddle Serving provides model encryption inference, This document shows the details.
We use symmetric encryption algorithm to encrypt the model. Symmetric encryption algorithm uses the same key for encryption and decryption, it has small amount of calculation, fast speed, is the most commonly used encryption method.
Normal model and parameters can be understood as a string, by using the encryption algorithm (parameter is your key) on them, the normal model and parameters become an encrypted one.
We provide a simple demo to encrypt the model. See the examples/C++/encryption/encrypt.py。
Suppose you already have an encrypted model(in the encrypt_server/
),you can start the encryption model service by adding an additional command line parameter --use_encryption_model
CPU Service
python -m paddle_serving_server.serve --model encrypt_server/ --port 9300 --use_encryption_model
GPU Service
python -m paddle_serving_server.serve --model encrypt_server/ --port 9300 --use_encryption_model --gpu_ids 0
At this point, the server does not really start, but waits for the key。
First of all, you got have the key which is used in the process of model encryption.
Then you can configure your client with the key, when you connect the server, this key will send to the server and the server will keep it.
Once the server gets the key, it uses the key to parse the model and starts the model prediction service.
Example of model encryption inference, See the examples/C++/encryption/。
此处可能存在不合适展示的内容,页面不予展示。您可通过相关编辑功能自查并修改。
如您确认内容无涉及 不当用语 / 纯广告导流 / 暴力 / 低俗色情 / 侵权 / 盗版 / 虚假 / 无价值内容或违法国家有关法律法规的内容,可点击提交进行申诉,我们将尽快为您处理。