diff --git a/train.py b/train.py
index 6d53739..50bc69d 100644
--- a/train.py
+++ b/train.py
@@ -14,15 +14,24 @@ args.data_url = '/home/work/user-job-dir/inputs/data/'
 args.train_url = '/home/work/user-job-dir/outputs/model/'
 2、在训练环境中，需要将数据集从obs拷贝到训练镜像中，训练完以后，需要将输出的模型拷贝到obs.
 将数据集从obs拷贝到训练镜像中：
-try:
-    mox.file.copy_parallel(obs_data_url, args.data_url)
-    print("Successfully Download {} to {}".format(obs_data_url,
-                                                    args.data_url))
-except Exception as e:
-    print('moxing download {} to {} failed: '.format(
-        obs_data_url, args.data_url) + str(e))
+
+    obs_data_url = args.data_url
+        args.data_url = '/home/work/user-job-dir/data/'
+        if not os.path.exists(args.data_url):
+            os.mkdir(args.data_url)
+    try:     
+        mox.file.copy_parallel(obs_data_url, args.data_url)
+        print("Successfully Download {} to {}".format(obs_data_url,
+                                                        args.data_url))
+    except Exception as e:
+        print('moxing download {} to {} failed: '.format(
+            obs_data_url, args.data_url) + str(e))
 
 将输出的模型拷贝到obs：
+    obs_train_url = args.train_url
+    args.train_url = '/home/work/user-job-dir/model/'
+    if not os.path.exists(args.train_url):
+            os.mkdir(args.train_url)
 try:
         mox.file.copy_parallel(args.train_url, obs_train_url)
         print("Successfully Upload {} to {}".format(args.train_url,
@@ -30,6 +39,7 @@ try:
     except Exception as e:
         print('moxing upload {} to {} failed: '.format(args.train_url,
                                                        obs_train_url) + str(e))
+
 """
 
 import os
@@ -51,11 +61,11 @@ parser = argparse.ArgumentParser(description='MindSpore Lenet Example')
 # data_url,train_url是固定用于在modelarts上训练的参数，表示数据集的路径和输出模型的路径
 parser.add_argument('--data_url',
                     help='path to training/inference dataset folder',
-                    default='./data')
+                    default='/home/work/user-job-dir/data/')
 
 parser.add_argument('--train_url',
                     help='model folder to save/load',
-                    default='./model')
+                    default='/home/work/user-job-dir/model/')
 
 parser.add_argument(
     '--device_target',
@@ -64,16 +74,7 @@ parser.add_argument(
     choices=['Ascend', 'GPU', 'CPU'],
     help='device where the code will be implemented (default: Ascend)')
 
-#用户可自定义的参数，dataset_path在示例中指向data_url，save_checkpoint_path指向train_url，在添加超参数时这两个参数可不添加，modelarts已经默认使用data_url和train_url
-parser.add_argument('--dataset_path',
-                    type=str,
-                    default="./Data",
-                    help='path where the dataset is saved')
-parser.add_argument('--save_checkpoint_path',
-                    type=str,
-                    default="./ckpt",
-                    help='if is test, must provide\
-                    path where the trained ckpt file')
+#modelarts已经默认使用data_url和train_url
 parser.add_argument('--epoch_size',
                     type=int,
                     default=5,
@@ -86,11 +87,18 @@ if __name__ == "__main__":
     args = parser.parse_args()
 
  ######################## 将数据集从obs拷贝到训练镜像中 （固定写法）########################   
-    # 在训练环境中定义data_url和train_url，并把数据从obs拷贝到相应的固定路径
+    # 在训练环境中定义data_url和train_url，并把数据从obs拷贝到相应的固定路径，以下写法是将数据拷贝到/home/work/user-job-dir/data/目录下，可修改为其他目录
+    #创建数据存放的位置
     obs_data_url = args.data_url
-    args.data_url = '/home/work/user-job-dir/inputs/data/'
+    args.data_url = '/home/work/user-job-dir/data/'  
+    if not os.path.exists(args.data_url):
+            os.mkdir(args.data_url)
+    #创建模型存放的位置
     obs_train_url = args.train_url
-    args.train_url = '/home/work/user-job-dir/outputs/model/'
+    args.train_url = '/home/work/user-job-dir/model/'
+    if not os.path.exists(args.train_url):
+            os.mkdir(args.train_url)
+    #将数据拷贝到训练环境
     try:
         mox.file.copy_parallel(obs_data_url, args.data_url)
         print("Successfully Download {} to {}".format(obs_data_url,
@@ -102,12 +110,11 @@ if __name__ == "__main__":
     
     #将dataset_path指向data_url，save_checkpoint_path指向train_url
     args.dataset_path = args.data_url
-    args.save_checkpoint_path = args.train_url
 
     context.set_context(mode=context.GRAPH_MODE,
                         device_target=args.device_target)
     #创建数据集
-    ds_train = create_dataset(os.path.join(args.dataset_path, "train"),
+    ds_train = create_dataset(os.path.join(args.data_url, "train"),
                               cfg.batch_size)
     if ds_train.get_dataset_size() == 0:
         raise ValueError(
@@ -135,7 +142,7 @@ if __name__ == "__main__":
         keep_checkpoint_max=cfg.keep_checkpoint_max)
     #定义模型输出路径
     ckpoint_cb = ModelCheckpoint(prefix="checkpoint_lenet",
-                                 directory=args.save_checkpoint_path,
+                                 directory=args.train_url,
                                  config=config_ck)
     #开始训练
     print("============== Starting Training ==============")