diff --git a/fluid/PaddleRec/ctr/cloud.py b/fluid/PaddleRec/ctr/cloud.py
deleted file mode 100644
index eaf18e2ba21053f20e372b1e88faee09ba40b924..0000000000000000000000000000000000000000
--- a/fluid/PaddleRec/ctr/cloud.py
+++ /dev/null
@@ -1,142 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-# ======================================================================
-#
-# Copyright (c) 2017 Baidu.com, Inc. All Rights Reserved
-#
-# ======================================================================
-
-import os
-
-import logging
-
-import hdfs_utils
-
-logging.basicConfig(
-    format='%(asctime)s - %(levelname)s - %(message)s')
-logger = logging.getLogger("cloud")
-logger.setLevel(logging.INFO)
-
-
-def run():
-    cmd = "python -u train.py "
-
-    cmd += " --train_data_path %s " % "data/train.txt"
-
-    cmd += " --test_data_path %s " % "data/test.txt"
-
-    if os.getenv("BATCH_SIZE", ""):
-        cmd += " --batch_size %s " % os.getenv("BATCH_SIZE")
-
-    if os.getenv("EMBEDDING_SIZE", ""):
-        cmd += " --embedding_size %s " % os.getenv("EMBEDDING_SIZE")
-
-    if os.getenv("NUM_PASSES", ""):
-        cmd += " --num_passes %s " % os.getenv("NUM_PASSES")
-
-    if os.getenv("MODEL_OUTPUT_DIR", ""):
-        cmd += " --model_output_dir %s " % os.getenv("MODEL_OUTPUT_DIR")
-
-    if os.getenv("SPARSE_FEATURE_DIM", ""):
-        cmd += " --sparse_feature_dim %s " % os.getenv("SPARSE_FEATURE_DIM")
-
-    if os.getenv("ASYNC_MODE", ""):
-        cmd += " --async_mode "
-
-    if os.getenv("NO_SPLIT_VAR", ""):
-        cmd += " --no_split_var "
-
-    is_local = int(os.getenv("PADDLE_IS_LOCAL", "1"))
-
-    if is_local:
-        cmd += " --is_local 1 "
-        cmd += " --cloud_train 0 "
-    else:
-        cmd += " --is_local 0 "
-        cmd += " --cloud_train 1 "
-
-        trainer_id = int(os.environ["PADDLE_TRAINER_ID"])
-        trainers = int(os.environ["PADDLE_TRAINERS"])
-        training_role = os.environ["PADDLE_TRAINING_ROLE"]
-
-        port = os.getenv("PADDLE_PSERVER_PORT", "6174")
-        pserver_ips = os.getenv("PADDLE_PSERVER_IPS", "")
-        eplist = []
-        for ip in pserver_ips.split(","):
-            eplist.append(':'.join([ip, port]))
-        pserver_endpoints = ",".join(eplist)
-        current_endpoint = os.getenv("PADDLE_CURRENT_IP", "") + ":" + port
-
-        if training_role == "PSERVER":
-            cmd += " --role pserver "
-        else:
-            cmd += " --role trainer "
-        cmd += " --endpoints %s " % pserver_endpoints
-        cmd += " --current_endpoint %s " % current_endpoint
-        cmd += " --trainer_id %s " % trainer_id
-        cmd += " --trainers %s " % trainers
-
-    logging.info("run cluster commands: {}".format(cmd))
-
-    exit(os.system(cmd))
-
-
-def download():
-    hadoop_home = os.getenv("HADOOP_HOME")
-
-    configs = {}
-    configs["fs.default.name"] = os.getenv("DATA_FS_NAME")
-    configs["hadoop.job.ugi"] = os.getenv("DATA_FS_UGI")
-    client = hdfs_utils.HDFSClient(hadoop_home, configs)
-
-    local_train_data_dir = os.getenv("TRAIN_DATA_LOCAL", "data")
-    hdfs_train_data_dir = os.getenv("TRAIN_DATA_HDFS", "")
-
-    downloads = hdfs_utils.multi_download(client, hdfs_train_data_dir, local_train_data_dir, 0, 1, multi_processes=1)
-
-    print(downloads)
-    for d in downloads:
-        base_dir = os.path.dirname(d)
-        tar_cmd = "tar -zxvf {} -C {}".format(d, base_dir)
-        print tar_cmd
-
-    for d in downloads:
-        base_dir = os.path.dirname(d)
-        tar_cmd = "tar -zxvf {} -C {}".format(d, base_dir)
-        logging.info("DOWNLOAD DATA: {}, AND TAR IT: {}".format(d, tar_cmd))
-        os.system(tar_cmd)
-
-
-def env_declar():
-    logging.info("********  Rename Cluster Env to PaddleFluid Env ********")
-
-    if os.environ["TRAINING_ROLE"] == "PSERVER" or os.environ["PADDLE_IS_LOCAL"] == "0":
-        os.environ["PADDLE_TRAINING_ROLE"] = os.environ["TRAINING_ROLE"]
-        os.environ["PADDLE_PSERVER_PORT"] = os.environ["PADDLE_PORT"]
-        os.environ["PADDLE_PSERVER_IPS"] = os.environ["PADDLE_PSERVERS"]
-        os.environ["PADDLE_TRAINERS"] = os.environ["PADDLE_TRAINERS_NUM"]
-        os.environ["PADDLE_CURRENT_IP"] = os.environ["POD_IP"]
-        os.environ["PADDLE_TRAINER_ID"] = os.environ["PADDLE_TRAINER_ID"]
-
-    os.environ["CPU_NUM"] = os.getenv("CPU_NUM", "12")
-    os.environ["NUM_THREADS"] = os.getenv("NUM_THREADS", "12")
-
-    logging.info("Content-Type: text/plain\n\n")
-    for key in os.environ.keys():
-        logging.info("%30s %s \n" % (key, os.environ[key]))
-
-    logging.info("******  Rename Cluster Env to PaddleFluid Env END ******")
-
-
-if __name__ == '__main__':
-    env_declar()
-
-    if os.getenv("NEED_CUSTOM_DOWNLOAD", ""):
-
-        if os.environ["PADDLE_TRAINING_ROLE"] == "PSERVER":
-            logging.info("PSERVER do not need to download datas")
-        else:
-            logging.info("NEED_CUSTOM_DOWNLOAD is True, will download train data with hdfs_utils")
-            download()
-
-    run()