add cloud

fluid/PaddleRec/ctr/README.cn.md

@@ -74,3 +74,6 @@ python infer.py \
 1. 用preprocess.py处理训练数据生成train.txt。
 1. 将train.txt切分成集群机器份，放到每台机器上。
 1. 用上面的 `分布式训练` 中的命令行启动分布式训练任务.
+
+## 在PaddleCloud上运行集群训练
+如果你正在使用PaddleCloud做集群训练，你可以使用```cloud.py```这个文件来帮助你提交任务，```trian.py```中所需要的参数可以通过PaddleCloud的环境变量来提交。
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fluid/PaddleRec/ctr/README.md

@@ -90,4 +90,7 @@ Note: The AUC value in the last log info is the total AUC for all test dataset.
 1. Please prepare some CPU machines on Baidu Cloud following the steps in [train_on_baidu_cloud](https://github.com/PaddlePaddle/FluidDoc/blob/develop/doc/fluid/user_guides/howto/training/train_on_baidu_cloud_cn.rst)
 1. Prepare dataset using preprocess.py.
 1. Split the train.txt to trainer_num parts and put them on the machines.
-1. Run training with the cluster train using the command in `Distributed Train` above.
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+1. Run training with the cluster train using the command in `Distributed Train` above.
+
+## Train on Paddle Cloud
+If you want to run this training on PaddleCloud, you can use the script ```cloud.py```, you can change the arguments in ```trian.py``` through environments in PaddleCloud.
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fluid/PaddleRec/ctr/cloud.py

@@ -5,12 +5,13 @@
 # Copyright (c) 2017 Baidu.com, Inc. All Rights Reserved
 #
 # ======================================================================
+"""this file is only for PaddleCloud"""
 
 import os
 
 import logging
 
-import hdfs_utils
+import paddle.fluid.contrib.utils.hdfs_utils as hdfs_utils
 
 logging.basicConfig(
     format='%(asctime)s - %(levelname)s - %(message)s')