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49 lines
2.0 KiB
Markdown
49 lines
2.0 KiB
Markdown
[English](README.md) | 中文
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# 使用FastDeploy生成加密模型
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本目录下提供`encrypt.py`快速完成ResNet50_vd的模型和参数文件加密
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FastDeploy支持对称加密的方案，通过调用OpenSSL中的对称加密算法（AES）对模型进行加密并产生密钥
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## 加密
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```bash
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#下载加密示例代码
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git clone https://github.com/PaddlePaddle/FastDeploy.git
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cd FastDeploy/tutorials/encrypt_model
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# 下载ResNet50_vd模型文件
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wget https://bj.bcebos.com/paddlehub/fastdeploy/ResNet50_vd_infer.tgz
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tar -xvf ResNet50_vd_infer.tgz
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python encrypt.py --model_file ResNet50_vd_infer/inference.pdmodel --params_file ResNet50_vd_infer/inference.pdiparams --encrypted_model_dir ResNet50_vd_infer_encrypt
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```
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>> **注意** 加密完成后会生成ResNet50_vd_infer_encrypt文件夹，包含`__model__.encrypted`,`__params__.encrypted`,`encryption_key.txt`三个文件，其中`encryption_key.txt`包含加密后的秘钥，同时需要将原文件夹中的、`inference_cls.yaml`配置文件 拷贝至ResNet50_vd_infer_encrypt文件夹，以便后续部署使用
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### Python加密接口
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通过如下接口的设定，使用加密接口（解密）
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```python
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import fastdeploy as fd
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import os
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# when key is not given, key will be automatically generated.
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# otherwise, the file will be encrypted by specific key
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encrypted_model, key = fd.encryption.encrypt(model_file.read())
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encrypted_params, key= fd.encryption.encrypt(params_file.read(), key)
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```
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### FastDeploy 部署加密模型
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通过如下接口的设定，完成加密模型的推理
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```python
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import fastdeploy as fd
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option = fd.RuntimeOption()
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option.set_encryption_key(key)
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```
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```C++
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fastdeploy::RuntimeOption option;
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option.SetEncryptionKey(key)
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```
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>> **注意** RuntimeOption的更多详细信息，请参考[RuntimeOption Python文档](https://www.paddlepaddle.org.cn/fastdeploy-api-doc/python/html/runtime_option.html)，[RuntimeOption C++文档](https://www.paddlepaddle.org.cn/fastdeploy-api-doc/cpp/html/structfastdeploy_1_1RuntimeOption.html)
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