update docker hub;fix plot bug, test=develop

01.fit_a_line/README.cn.md

@@ -223,16 +223,16 @@ for pass_id in range(num_epochs):
                                   feed=feeder.feed(data_train),
                                   fetch_list=[avg_loss])
         if step % 10 == 0:  # record a train cost every 10 batches
-            plot_cost.append(train_prompt, step, avg_loss_value[0])
-            plot_cost.plot()
+            plot_prompt.append(train_prompt, step, avg_loss_value[0])
+            plot_prompt.plot()
         if step % 100 == 0:  # record a test cost every 100 batches
             test_metics = train_test(executor=exe_test,
                                      program=test_program,
                                      reader=test_reader,
                                      fetch_list=[avg_loss.name],
                                      feeder=feeder)
-            plot_cost.append(test_prompt, step, test_metics[0])
-            plot_cost.plot()
+            plot_prompt.append(test_prompt, step, test_metics[0])
+            plot_prompt.plot()
             # If the accuracy is good enough, we can stop the training.
             if test_metics[0] < 10.0:
                 break

01.fit_a_line/index.cn.html

@@ -265,16 +265,16 @@ for pass_id in range(num_epochs):
                                   feed=feeder.feed(data_train),
                                   fetch_list=[avg_loss])
         if step % 10 == 0:  # record a train cost every 10 batches
-            plot_cost.append(train_prompt, step, avg_loss_value[0])
-            plot_cost.plot()
+            plot_prompt.append(train_prompt, step, avg_loss_value[0])
+            plot_prompt.plot()
         if step % 100 == 0:  # record a test cost every 100 batches
             test_metics = train_test(executor=exe_test,
                                      program=test_program,
                                      reader=test_reader,
                                      fetch_list=[avg_loss.name],
                                      feeder=feeder)
-            plot_cost.append(test_prompt, step, test_metics[0])
-            plot_cost.plot()
+            plot_prompt.append(test_prompt, step, test_metics[0])
+            plot_prompt.plot()
             # If the accuracy is good enough, we can stop the training.
             if test_metics[0] < 10.0:
                 break

README.cn.md

@@ -29,10 +29,10 @@ docker run -d -p 8888:8888 paddlepaddle/book
 
 会从DockerHub.com下载和运行本书的Docker image。阅读和在线编辑本书请在浏览器里访问 http://localhost:8888 。
 
-如果您访问DockerHub.com很慢，可以试试我们的另一个镜像docker.paddlepaddlehub.com：
+如果您访问DockerHub.com很慢，可以试试我们的另一个镜像hub.baidubce.com：
 
 ```bash
-docker run -d -p 8888:8888 docker.paddlepaddlehub.com/book
+docker run -d -p 8888:8888 hub.baidubce.com/paddlepaddle/book
 ```
 
 ### 使用GPU训练
@@ -46,7 +46,7 @@ nvidia-docker run -d -p 8888:8888 paddlepaddle/book:latest-gpu
 或者使用国内的镜像请运行：
 
 ```bash
-nvidia-docker run -d -p 8888:8888 docker.paddlepaddlehub.com/book:latest-gpu
+nvidia-docker run -d -p 8888:8888 hub.baidubce.com/paddlepaddle/book:latest-gpu
 ```
 
 还需要将以下代码

README.md

@@ -28,10 +28,10 @@ docker run -d -p 8888:8888 paddlepaddle/book
 
 This command will download the pre-built Docker image from DockerHub.com and run it in a container.  Please direct your Web browser to http://localhost:8888 to read the book.
 
-If you are living in somewhere slow to access DockerHub.com, you might try our mirror server docker.paddlepaddlehub.com:
+If you are living in somewhere slow to access DockerHub.com, you might try our mirror server hub.baidubce.com:
 
 ```bash
-docker run -d -p 8888:8888 docker.paddlepaddlehub.com/book
+docker run -d -p 8888:8888 hub.baidubce.com/paddlepaddle/book
 
 ```
 
@@ -49,7 +49,7 @@ nvidia-docker run -d -p 8888:8888 paddlepaddle/book:latest-gpu
 Or you can use the image registry mirror in China:
 
 ```bash
-nvidia-docker run -d -p 8888:8888 docker.paddlepaddlehub.com/book:latest-gpu
+nvidia-docker run -d -p 8888:8888 hub.baidubce.com/paddlepaddle/book:latest-gpu
 
 ```