Merge pull request #1059 from HexToString/fix_encoding_bug

fix doc and delete unused file

doc/GRPC_IMPL_CN.md

@@ -115,24 +115,12 @@ python test_asyn_client.py
 python test_batch_client.py
 ```
 
-#### 通用 pb 预测
-
-``` shell
-python test_general_pb_client.py
-```
-
 #### 预测超时
 
 ``` shell
 python test_timeout_client.py
 ```
 
-#### List 输入
-
-``` shell
-python test_list_input_client.py
-```
-
 ## 3.更多示例
 
 详见[`python/examples/grpc_impl_example`](../python/examples/grpc_impl_example)下的示例文件。

doc/JAVA_SDK.md

@@ -18,7 +18,7 @@ The following table shows compatibilities between Paddle Serving Server and Java
 
 | Paddle Serving Server version | Java SDK version |
 | :---------------------------: | :--------------: |
-|             0.3.2             |      0.0.1       |
+|             0.5.0             |      0.0.1       |
 
 1.    Directly use the provided Java SDK as the client for prediction
 ### Install Java SDK

doc/JAVA_SDK_CN.md

@@ -17,7 +17,7 @@ Paddle Serving 提供了 Java SDK，支持 Client 端用 Java 语言进行预测
 
 | Paddle Serving Server version | Java SDK version |
 | :---------------------------: | :--------------: |
-|             0.3.2             |      0.0.1       |
+|             0.5.0             |      0.0.1       |
 
 1.    直接使用提供的Java SDK作为Client进行预测
 ### 安装

python/examples/fit_a_line/test_numpy_input_client.py

-# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved.
-#
-# Licensed under the Apache License, Version 2.0 (the "License");
-# you may not use this file except in compliance with the License.
-# You may obtain a copy of the License at
-#
-#     http://www.apache.org/licenses/LICENSE-2.0
-#
-# Unless required by applicable law or agreed to in writing, software
-# distributed under the License is distributed on an "AS IS" BASIS,
-# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
-# See the License for the specific language governing permissions and
-# limitations under the License.
-# pylint: disable=doc-string-missing
-
-from paddle_serving_client import Client
-import numpy as np
-import sys
-
-client = Client()
-client.load_client_config(sys.argv[1])
-client.connect(["127.0.0.1:9393"])
-
-import paddle
-test_reader = paddle.batch(
-    paddle.reader.shuffle(
-        paddle.dataset.uci_housing.test(), buf_size=500),
-    batch_size=1)
-
-for data in test_reader():
-    fetch_map = client.predict(
-        feed={"x": np.array(data[0][0])}, fetch=["price"])
-    print("{} {}".format(fetch_map["price"][0][0], data[0][1][0]))