fix client ip

java/README_CN.md

@@ -98,7 +98,7 @@ java -cp paddle-serving-sdk-java-examples-0.0.1-jar-with-dependencies.jar Pipeli
 
 ### 注意事项
 
-1.在示例中，端口号都是9393，ip默认设置为了0.0.0.0表示本机，注意ip和port需要与Server端对应。
+1.在示例中，端口号都是9393，ip默认设置为了127.0.0.1表示本机，注意ip和port需要与Server端对应。
 
 2.目前Serving已推出Pipeline模式（原理详见[Pipeline Serving](../doc/PIPELINE_SERVING_CN.md)），面向Java的Pipeline Serving Client已发布。
 

java/examples/src/main/java/PaddleServingClientExample.java

@@ -25,7 +25,7 @@ public class PaddleServingClientExample {
         List<String> fetch = Arrays.asList("price");
         
         Client client = new Client();
-        client.setIP("0.0.0.0");
+        client.setIP("127.0.0.1");
         client.setPort("9393");
         client.loadClientConfig(model_config_path);
         String result = client.predict(feed_data, fetch, true, 0);
@@ -49,7 +49,7 @@ public class PaddleServingClientExample {
         
         Client client = new Client();
         //注意：跨docker，需要设置--net-host或直接访问另一个docker的ip
-        client.setIP("0.0.0.0");
+        client.setIP("127.0.0.1");
         client.setPort("9393");
         client.set_http_proto(false);
         client.loadClientConfig(model_config_path);
@@ -73,7 +73,7 @@ public class PaddleServingClientExample {
         List<String> fetch = Arrays.asList("price");
         
         Client client = new Client();
-        client.setIP("0.0.0.0");
+        client.setIP("127.0.0.1");
         client.setPort("9393");
         client.loadClientConfig(model_config_path);
         client.set_use_grpc_client(true);
@@ -97,7 +97,7 @@ public class PaddleServingClientExample {
         List<String> fetch = Arrays.asList("price");
         
         Client client = new Client();
-        client.setIP("0.0.0.0");
+        client.setIP("127.0.0.1");
         client.setPort("9393");
         client.loadClientConfig(model_config_path);
         client.use_key(keyFilePath);
@@ -125,7 +125,7 @@ public class PaddleServingClientExample {
         List<String> fetch = Arrays.asList("price");
         
         Client client = new Client();
-        client.setIP("0.0.0.0");
+        client.setIP("127.0.0.1");
         client.setPort("9393");
         client.loadClientConfig(model_config_path);
         client.set_request_compress(true);
@@ -176,7 +176,7 @@ public class PaddleServingClientExample {
             }};
         List<String> fetch = Arrays.asList("save_infer_model/scale_0.tmp_0");
         Client client = new Client();
-        client.setIP("0.0.0.0");
+        client.setIP("127.0.0.1");
         client.setPort("9393");
         client.loadClientConfig(model_config_path);
         String result = client.predict(feed_data, fetch, true, 0);
@@ -198,7 +198,7 @@ public class PaddleServingClientExample {
             }};
         List<String> fetch = Arrays.asList("pooled_output");
         Client client = new Client();
-        client.setIP("0.0.0.0");
+        client.setIP("127.0.0.1");
         client.setPort("9393");
         client.loadClientConfig(model_config_path);
         String result = client.predict(feed_data, fetch, true, 0);
@@ -268,7 +268,7 @@ public class PaddleServingClientExample {
             }};
         List<String> fetch = Arrays.asList("prob");
         Client client = new Client();
-        client.setIP("0.0.0.0");
+        client.setIP("127.0.0.1");
         client.setPort("9393");
         client.loadClientConfig(model_config_path);
         String result = client.predict(feed_data, fetch, true, 0);

java/src/main/java/io/paddle/serving/client/Client.java

@@ -134,7 +134,7 @@ public class Client {
         feedTensorLen_ = null;
         feedNameToIndex_ = null;
         timeoutS_ = 200000;
-        ip = "0.0.0.0";
+        ip = "127.0.0.1";
         port = "9393";
         serverPort = "9393";
         serviceName = "/GeneralModelService/inference";

python/paddle_serving_client/httpclient.py

@@ -75,7 +75,7 @@ def data_bytes_number(datalist):
 # 或者直接调用grpc_client_predict()
 class HttpClient(object):
     def __init__(self,
-                 ip="0.0.0.0",
+                 ip="127.0.0.1",
                  port="9393",
                  service_name="/GeneralModelService/inference"):
         self.feed_names_ = []

python/paddle_serving_server/serve.py

@@ -37,7 +37,7 @@ import socket
 def port_is_available(port):
     with closing(socket.socket(socket.AF_INET, socket.SOCK_STREAM)) as sock:
         sock.settimeout(2)
-        result = sock.connect_ex(('0.0.0.0', port))
+        result = sock.connect_ex(('127.0.0.1', port))
     if result != 0:
         return True
     else:

python/paddle_serving_server/server.py

@@ -537,7 +537,7 @@ class Server(object):
     def port_is_available(self, port):
         with closing(socket.socket(socket.AF_INET, socket.SOCK_STREAM)) as sock:
             sock.settimeout(2)
-            result = sock.connect_ex(('0.0.0.0', port))
+            result = sock.connect_ex(('127.0.0.1', port))
         if result != 0:
             return True
         else:

python/paddle_serving_server/web_service.py

@@ -33,7 +33,7 @@ from paddle_serving_server.serve import format_gpu_to_strlist
 def port_is_available(port):
     with closing(socket.socket(socket.AF_INET, socket.SOCK_STREAM)) as sock:
         sock.settimeout(2)
-        result = sock.connect_ex(('0.0.0.0', port))
+        result = sock.connect_ex(('127.0.0.1', port))
     if result != 0:
         return True
     else:

python/pipeline/util.py

@@ -39,7 +39,7 @@ class AvailablePortGenerator(object):
     def port_is_available(port):
         with closing(socket.socket(socket.AF_INET, socket.SOCK_STREAM)) as sock:
             sock.settimeout(2)
-            result = sock.connect_ex(('0.0.0.0', port))
+            result = sock.connect_ex(('127.0.0.1', port))
         if result != 0:
             return True
         else: