support 3 types and fix httpClient

paddle_inference/paddle/include/paddle_engine.h

@@ -70,7 +70,7 @@ PrecisionType GetPrecision(const std::string& precision_data) {
   return PrecisionType::kFloat32;
 }
 
-const std::string& getFileBySuffix(
+const std::string getFileBySuffix(
     const std::string& path, const std::vector<std::string>& suffixVector) {
   DIR* dp = nullptr;
   std::string fileName = "";
@@ -156,9 +156,21 @@ class PaddleInferenceEngine : public EngineCore {
     }
 
     Config config;
-    // todo, auto config(zhangjun)
-    if (engine_conf.has_encrypted_model() && engine_conf.encrypted_model()) {
+    std::vector<std::string> suffixParaVector = {".pdiparams", "__params__"};
+    std::vector<std::string> suffixModelVector = {".pdmodel", "__model__"};
+    std::string paraFileName = getFileBySuffix(model_path, suffixParaVector);
+    std::string modelFileName = getFileBySuffix(model_path, suffixModelVector);
+
+    std::string encryParaPath = model_path + "/encrypt_model";
+    std::string encryModelPath = model_path + "/encrypt_params";
+    std::string encryKeyPath = model_path + "/key";
+
+    // encrypt model
+    if (access(encryParaPath.c_str(), F_OK) != -1 &&
+        access(encryModelPath.c_str(), F_OK) != -1 &&
+        access(encryKeyPath.c_str(), F_OK) != -1) {
       // decrypt model
+
       std::string model_buffer, params_buffer, key_buffer;
       predictor::ReadBinaryFile(model_path + "/encrypt_model", &model_buffer);
       predictor::ReadBinaryFile(model_path + "/encrypt_params", &params_buffer);
@@ -172,19 +184,11 @@ class PaddleInferenceEngine : public EngineCore {
                             real_model_buffer.size(),
                             &real_params_buffer[0],
                             real_params_buffer.size());
-    } else if (engine_conf.has_combined_model() &&
-               (!engine_conf.combined_model())) {
-      config.SetModel(model_path);
-    } else {
-      std::vector<std::string> suffixParaVector = {".pdiparams", "__params__"};
-      std::vector<std::string> suffixModelVector = {".pdmodel", "__model__"};
-      std::string paraFileName = getFileBySuffix(model_path, suffixParaVector);
-      std::string modelFileName =
-          getFileBySuffix(model_path, suffixModelVector);
-      if (paraFileName.length() != 0 && modelFileName.length() != 0) {
+    } else if (paraFileName.length() != 0 && modelFileName.length() != 0) {
       config.SetParamsFile(model_path + "/" + paraFileName);
       config.SetProgFile(model_path + "/" + modelFileName);
-      }
+    } else {
+      config.SetModel(model_path);
     }
 
     config.SwitchSpecifyInputNames(true);

python/paddle_serving_client/httpclient.py

@@ -403,7 +403,7 @@ class HttpClient(object):
             # 由于输入比较特殊，shape保持原feedvar中不变
             data_value = []
             data_value.append(feed_dict[key])
-            if isinstance(feed_dict[key], str):
+            if isinstance(feed_dict[key], (str, bytes)):
                 if self.feed_types_[key] != bytes_type:
                     raise ValueError(
                         "feedvar is not string-type,feed can`t be a single string."
@@ -411,7 +411,7 @@ class HttpClient(object):
             else:
                 if self.feed_types_[key] == bytes_type:
                     raise ValueError(
-                        "feedvar is string-type,feed, feed can`t be a single int or others."
+                        "feedvar is string-type,feed can`t be a single int or others."
                     )
         # 如果不压缩，那么不需要统计数据量。
         if self.try_request_gzip: