Merge branch 'develop' into matting

fastdeploy/runtime/option_pybind.cc

@@ -35,6 +35,7 @@ void BindOption(pybind11::module& m) {
       .def(pybind11::init())
       .def("set_model_path", &RuntimeOption::SetModelPath)
       .def("set_model_buffer", &RuntimeOption::SetModelBuffer)
+      .def("set_encryption_key", &RuntimeOption::SetEncryptionKey)
       .def("use_gpu", &RuntimeOption::UseGpu)
       .def("use_cpu", &RuntimeOption::UseCpu)
       .def("use_rknpu2", &RuntimeOption::UseRKNPU2)

fastdeploy/runtime/runtime.cc

@@ -104,7 +104,33 @@ bool AutoSelectBackend(RuntimeOption& option) {
 
 bool Runtime::Init(const RuntimeOption& _option) {
   option = _option;
-
+  // decrypt encrypted model
+  if ("" != option.encryption_key_) {
+#ifdef ENABLE_ENCRYPTION
+    if (option.model_from_memory_) {
+      option.model_file = Decrypt(option.model_file, option.encryption_key_);
+      if (!(option.params_file.empty())) {
+        option.params_file =
+            Decrypt(option.params_file, option.encryption_key_);
+      }
+    } else {
+      std::string model_buffer = "";
+      FDASSERT(ReadBinaryFromFile(option.model_file, &model_buffer),
+               "Fail to read binary from model file");
+      option.model_file = Decrypt(model_buffer, option.encryption_key_);
+      if (!(option.params_file.empty())) {
+        std::string params_buffer = "";
+        FDASSERT(ReadBinaryFromFile(option.params_file, &params_buffer),
+                 "Fail to read binary from parameter file");
+        option.params_file = Decrypt(params_buffer, option.encryption_key_);
+      }
+      option.model_from_memory_ = true;
+    }
+#else
+    FDERROR << "The FastDeploy didn't compile with encryption function."
+            << std::endl;
+#endif
+  }
   // Choose default backend by model format and device if backend is not
   // specified
   if (option.backend == Backend::UNKNOWN) {

fastdeploy/runtime/runtime.h

@@ -23,6 +23,9 @@
 #include "fastdeploy/core/fd_tensor.h"
 #include "fastdeploy/runtime/runtime_option.h"
 #include "fastdeploy/utils/perf.h"
+#ifdef ENABLE_ENCRYPTION
+#include "fastdeploy/encryption/include/decrypt.h"
+#endif
 
 /** \brief All C++ FastDeploy APIs are defined inside this namespace
 *

fastdeploy/runtime/runtime_option.cc

@@ -36,6 +36,15 @@ void RuntimeOption::SetModelBuffer(const std::string& model_buffer,
   model_from_memory_ = true;
 }
 
+void RuntimeOption::SetEncryptionKey(const std::string& encryption_key) {
+#ifdef ENABLE_ENCRYPTION
+  encryption_key_ = encryption_key;
+#else
+  FDERROR << "The FastDeploy didn't compile with encryption function."
+          << std::endl;
+#endif
+}
+
 void RuntimeOption::UseGpu(int gpu_id) {
 #ifdef WITH_GPU
   device = Device::GPU;

fastdeploy/runtime/runtime_option.h

@@ -59,6 +59,12 @@ struct FASTDEPLOY_DECL RuntimeOption {
                       const std::string& params_buffer = "",
                       const ModelFormat& format = ModelFormat::PADDLE);
 
+  /** \brief When loading encrypted model, encryption_key is required to decrypte model
+   *
+   * \param[in] encryption_key The key for decrypting model
+   */
+  void SetEncryptionKey(const std::string& encryption_key);
+
   /// Use cpu to inference, the runtime will inference on CPU by default
   void UseCpu();
   /// Use Nvidia GPU to inference
@@ -178,6 +184,8 @@ struct FASTDEPLOY_DECL RuntimeOption {
   /// format of input model
   ModelFormat model_format = ModelFormat::PADDLE;
 
+  std::string encryption_key_ = "";
+
   // for cpu inference
   // default will let the backend choose their own default value
   int cpu_thread_num = -1;

python/fastdeploy/runtime.py

@@ -187,6 +187,12 @@ class RuntimeOption:
         return self._option.set_model_buffer(model_buffer, params_buffer,
                                              model_format)
 
+    def set_encryption_key(self, encryption_key):
+        """When loading encrypted model, encryption_key is required to decrypte model
+        :param encryption_key: (str)The key for decrypting model
+        """
+        return self._option.set_encryption_key(encryption_key)
+
     def use_gpu(self, device_id=0):
         """Inference with Nvidia GPU
 
@@ -583,9 +589,11 @@ class RuntimeOption:
                        replica_num=1,
                        available_memory_proportion=1.0,
                        enable_half_partial=False):
-        logging.warning("`RuntimeOption.set_ipu_config` will be deprecated in v1.2.0, please use `RuntimeOption.paddle_infer_option.set_ipu_config()` instead.")
+        logging.warning(
-        self._option.paddle_infer_option.set_ipu_config(enable_fp16, replica_num,
+            "`RuntimeOption.set_ipu_config` will be deprecated in v1.2.0, please use `RuntimeOption.paddle_infer_option.set_ipu_config()` instead."
-                                           available_memory_proportion,
+        )
+        self._option.paddle_infer_option.set_ipu_config(
+            enable_fp16, replica_num, available_memory_proportion,
             enable_half_partial)
 
     @property
@@ -657,7 +665,8 @@ class RuntimeOption:
                 continue
             if hasattr(getattr(self._option, attr), "__call__"):
                 continue
-            message += "  {} : {}\t\n".format(attr, getattr(self._option, attr))
+            message += "  {} : {}\t\n".format(attr,
+                                              getattr(self._option, attr))
         message.strip("\n")
         message += ")"
         return message

tutorials/encrypt_model/README.md

@@ -0,0 +1,46 @@
+English | [中文](README_CN.md)
+
+# FastDeploy generates an encrypted model
+
+This directory provides `encrypt.py` to quickly complete the encryption of the model and parameter files of ResNet50_vd
+
+## encryption
+```bash
+# Download deployment example code
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd  FastDeploy/tutorials/encrypt_model
+
+# Download the ResNet50_vd model file
+wget https://bj.bcebos.com/paddlehub/fastdeploy/ResNet50_vd_infer.tgz
+tar -xvf ResNet50_vd_infer.tgz
+
+python encrypt.py --model_file ResNet50_vd_infer/inference.pdmodel  --params_file ResNet50_vd_infer/inference.pdiparams --encrypted_model_dir ResNet50_vd_infer_encrypt
+```
+>> **Note** After the encryption is completed, the ResNet50_vd_infer_encrypt folder will be generated, including `__model__.encrypted`, `__params__.encrypted`, `encryption_key.txt` three files, where `encryption_key.txt` contains the encrypted key. At the same time, you need to copy the `inference_cls.yaml` configuration file in the original folder to the ResNet50_vd_infer_encrypt folder for subsequent deployment
+
+### Python encryption interface
+
+Use the encrypted interface through the following interface settings
+```python
+import fastdeploy as fd
+import os
+# when key is not given, key will be automatically generated.
+# otherwise, the file will be encrypted by specific key
+encrypted_model, key = fd.encryption.encrypt(model_file.read())
+encrypted_params, key= fd.encryption.encrypt(params_file.read(), key)
+```
+
+### FastDeploy deployment encryption model (decryption)
+
+Through the setting of the following interface, FastDeploy can deploy the encryption model
+```python
+import fastdeploy as fd
+option = fd.RuntimeOption()
+option.set_encryption_key(key)
+```
+
+```C++
+fastdeploy::RuntimeOption option;
+option.SetEncryptionKey(key)
+```
+>> **Note** For more details about RuntimeOption, please refer to [RuntimeOption Python Documentation](https://www.paddlepaddle.org.cn/fastdeploy-api-doc/python/html/runtime_option.html), [ RuntimeOption C++ Documentation](https://www.paddlepaddle.org.cn/fastdeploy-api-doc/cpp/html/structfastdeploy_1_1RuntimeOption.html)

tutorials/encrypt_model/README_CN.md

@@ -0,0 +1,48 @@
+[English](README.md) | 中文
+
+# 使用FastDeploy生成加密模型
+
+本目录下提供`encrypt.py`快速完成ResNet50_vd的模型和参数文件加密
+
+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
+
+## 加密
+```bash
+#下载加密示例代码
+git clone https://github.com/PaddlePaddle/FastDeploy.git
+cd  FastDeploy/tutorials/encrypt_model
+
+# 下载ResNet50_vd模型文件
+wget https://bj.bcebos.com/paddlehub/fastdeploy/ResNet50_vd_infer.tgz
+tar -xvf ResNet50_vd_infer.tgz
+
+python encrypt.py --model_file ResNet50_vd_infer/inference.pdmodel  --params_file ResNet50_vd_infer/inference.pdiparams --encrypted_model_dir ResNet50_vd_infer_encrypt
+```
+>> **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
+
+### Python加密接口
+
+通过如下接口的设定，使用加密接口（解密）
+```python
+import fastdeploy as fd
+import os
+# when key is not given, key will be automatically generated.
+# otherwise, the file will be encrypted by specific key
+encrypted_model, key = fd.encryption.encrypt(model_file.read())
+encrypted_params, key= fd.encryption.encrypt(params_file.read(), key)
+```
+
+### FastDeploy 部署加密模型
+
+通过如下接口的设定，完成加密模型的推理
+```python
+import fastdeploy as fd
+option = fd.RuntimeOption()
+option.set_encryption_key(key)
+```
+
+```C++
+fastdeploy::RuntimeOption option;
+option.SetEncryptionKey(key)
+```
+>> **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)

tutorials/encrypt_model/encrypt.py

@@ -0,0 +1,47 @@
+import fastdeploy as fd
+import os
+
+
+def parse_arguments():
+    import argparse
+    import ast
+    parser = argparse.ArgumentParser()
+    parser.add_argument(
+        "--encrypted_model_dir",
+        required=False,
+        help="Path of model directory.")
+    parser.add_argument(
+        "--model_file", required=True, help="Path of model file directory.")
+    parser.add_argument(
+        "--params_file",
+        required=True,
+        help="Path of parameters file directory.")
+    return parser.parse_args()
+
+
+if __name__ == "__main__":
+    args = parse_arguments()
+    model_buffer = open(args.model_file, 'rb')
+    params_buffer = open(args.params_file, 'rb')
+    encrypted_model, key = fd.encryption.encrypt(model_buffer.read())
+    # use the same key to encrypt parameter file
+    encrypted_params, key = fd.encryption.encrypt(params_buffer.read(), key)
+    encrypted_model_dir = "encrypt_model_dir"
+    if args.encrypted_model_dir:
+        encrypted_model_dir = args.encrypted_model_dir
+    model_buffer.close()
+    params_buffer.close()
+    os.mkdir(encrypted_model_dir)
+    with open(os.path.join(encrypted_model_dir, "__model__.encrypted"),
+              "w") as f:
+        f.write(encrypted_model)
+
+    with open(os.path.join(encrypted_model_dir, "__params__.encrypted"),
+              "w") as f:
+        f.write(encrypted_params)
+
+    with open(os.path.join(encrypted_model_dir, "encryption_key.txt"),
+              "w") as f:
+        f.write(key)
+    print("encryption key: ", key)
+    print("encryption success")