Merge branch 'develop' of https://github.com/PaddlePaddle/Serving into ensemble-support

doc/UWSGI_DEPLOY.md

+# 使用uwsgi启动HTTP预测服务
+
+在提供的fit_a_line示例中，启动HTTP预测服务后会看到有以下信息：
+
+```shell
+web service address:
+http://10.127.3.150:9393/uci/prediction
+ * Serving Flask app "serve" (lazy loading)
+ * Environment: production
+   WARNING: This is a development server. Do not use it in a production deployment.
+   Use a production WSGI server instead.
+ * Debug mode: off
+ * Running on http://0.0.0.0:9393/ (Press CTRL+C to quit)
+```
+
+这里会提示启动的HTTP服务是开发模式，并不能用于生产环境的部署。Flask启动的服务环境不够稳定也无法承受大量请求的并发，实际部署过程中配合需要WSGI（Web Server Gateway Interface）使用。
+
+下面我们展示一下如何使用[uWSGI](https://github.com/unbit/uwsgi)模块来部署HTTP预测服务用于生产环境。
+
+编写HTTP服务脚本
+
+```python
+#uwsgi_service.py
+from paddle_serving_server.web_service import WebService
+from flask import Flask, request
+
+#配置预测服务
+uci_service = WebService(name = "uci")
+uci_service.load_model_config("./uci_housing_model")
+uci_service.prepare_server(workdir="./workdir", port=int(9500), device="cpu")
+uci_service.run_server()
+
+#配置flask服务
+app_instance = Flask(__name__)
+@app_instance.before_first_request
+def init():
+    global uci_service
+    uci_service._launch_web_service()
+
+service_name = "/" + uci_service.name + "/prediction"
+@app_instance.route(service_name, methods=["POST"])
+def run():
+    return uci_service.get_prediction(request)
+
+#run方法用于直接调试中直接启动服务
+if __name__ == "__main__":
+    app_instance.run()
+```
+
+使用uwsgi启动HTTP服务
+
+```bash
+uwsgi --http :9000 --wsgi-file uwsgi_service.py --callable app_instance --processes 4
+```
+
+使用--processes参数可以指定服务的进程数，请注意目前Serving HTTP 服务暂时不支持多线程的方式使用。
+
+更多uWSGI的信息请参考[uWSGI使用文档](https://uwsgi-docs.readthedocs.io/en/latest/)

python/paddle_serving_client/__init__.py

@@ -18,7 +18,6 @@ import os
 from .proto import sdk_configure_pb2 as sdk
 from .proto import general_model_config_pb2 as m_config
 import google.protobuf.text_format
-import time
 import sys
 
 int_type = 0
@@ -156,8 +155,7 @@ class Client(object):
                 )
         else:
             if self.predictor_sdk_ is None:
-                timestamp = time.time()
-                self.add_variant('default_tag_{}'.format(timestamp), endpoints,
+                self.add_variant('default_tag_{}'.format(id(self)), endpoints,
                                  100)
             else:
                 print(