diff --git a/official/cv/alexnet/README.md b/official/cv/alexnet/README.md
index 8e83818bfdcc0af7e348dd6feaeb6d42380303f1..4f5d225589424e50ea4c23c01a7dfdb0b45420ce 100644
--- a/official/cv/alexnet/README.md
+++ b/official/cv/alexnet/README.md
@@ -68,12 +68,12 @@ After installing MindSpore via the official website, you can start training and
 
 ```python
 # enter script dir, train AlexNet
-bash run_standalone_train_ascend.sh [DATA_PATH] [CKPT_SAVE_PATH]
-# example: bash run_standalone_train_ascend.sh /home/DataSet/Cifar10/cifar-10-batches-bin/ /home/model/alexnet/ckpt/
+bash run_standalone_train_ascend.sh [cifar10|imagenet] [DATA_PATH] [DEVICE_ID] [CKPT_PATH]
+# example: bash run_standalone_train_ascend.sh cifar10 /home/DataSet/Cifar10/cifar-10-batches-bin/ 0 /home/model/alexnet/ckpt/
 
 # enter script dir, evaluate AlexNet
-bash run_standalone_eval_ascend.sh [DATA_PATH] [CKPT_NAME]
-# example: bash run_standalone_eval_ascend.sh /home/DataSet/cifar10/cifar-10-verify-bin /home/model/cv/alxnet/ckpt/checkpoint_alexnet-1_1562.ckpt
+bash run_standalone_eval_ascend.sh [cifar10|imagenet] [DATA_PATH] [CKPT_NAME] [DEVICE_ID]
+# example: bash run_standalone_eval_ascend.sh cifar10 /home/DataSet/cifar10/cifar-10-verify-bin /home/model/cv/alxnet/ckpt/checkpoint_alexnet-1_1562.ckpt 0
 ```
 
 - Running on [ModelArts](https://support.huaweicloud.com/modelarts/)
@@ -231,7 +231,7 @@ Major parameters in train.py and config.py as follows:
   ```bash
   python train.py --config_path default_config.yaml --data_path cifar-10-batches-bin --ckpt_path ckpt > log 2>&1 &
   # or enter script dir, and run the script
-  bash run_standalone_train_ascend.sh /home/DataSet/Cifar10/cifar-10-batches-bin/ /home/model/alexnet/ckpt/
+  bash run_standalone_train_ascend.sh cifar10 /home/DataSet/Cifar10/cifar-10-batches-bin/ 0 /home/model/alexnet/ckpt/
   ```
 
   After training, the loss value will be achieved as follows:
@@ -253,7 +253,7 @@ Major parameters in train.py and config.py as follows:
   ```bash
   python train.py --config_path default_config.yaml --device_target "GPU" --data_path cifar-10-batches-bin --ckpt_path ckpt > log 2>&1 &
   # or enter script dir, and run the script
-  bash run_standalone_train_for_gpu.sh cifar-10-batches-bin ckpt
+  bash run_standalone_train_gpu.sh cifar10 cifar-10-batches-bin ckpt
   ```
 
   After training, the loss value will be achieved as follows:
@@ -278,7 +278,7 @@ Before running the command below, please check the checkpoint path used for eval
   ```bash
   python eval.py --config_path default_config.yaml --data_path cifar-10-verify-bin --ckpt_path ckpt/checkpoint_alexnet-1_1562.ckpt > eval_log.txt 2>&1 &
   # or enter script dir, and run the script
-  bash run_standalone_eval_ascend.sh cifar-10-verify-bin ckpt/checkpoint_alexnet-1_1562.ckpt
+  bash run_standalone_eval_ascend.sh cifar10 cifar-10-verify-bin ckpt/checkpoint_alexnet-1_1562.ckpt 0
   ```
 
   You can view the results through the file "eval_log". The accuracy of the test dataset will be as follows:
@@ -293,7 +293,7 @@ Before running the command below, please check the checkpoint path used for eval
   ```bash
   python eval.py --config_path default_config.yaml --device_target "GPU" --data_path cifar-10-verify-bin --ckpt_path ckpt/checkpoint_alexnet-30_1562.ckpt > eval_log 2>&1 &
   # or enter script dir, and run the script
-  bash run_standalone_eval_for_gpu.sh cifar-10-verify-bin ckpt/checkpoint_alexnet-30_1562.ckpt
+  bash run_standalone_eval_gpu.sh cifar10 cifar-10-verify-bin ckpt/checkpoint_alexnet-30_1562.ckpt 0
   ```
 
   You can view the results through the file "eval_log". The accuracy of the test dataset will be as follows:
diff --git a/official/cv/alexnet/README_CN.md b/official/cv/alexnet/README_CN.md
index 17873e1a24839303151beaaa3e676a9f83e5569b..aff8516744a6c1850a3aa330aec4df0152a60685 100644
--- a/official/cv/alexnet/README_CN.md
+++ b/official/cv/alexnet/README_CN.md
@@ -70,14 +70,14 @@ AlexNet鐢�5涓嵎绉眰鍜�3涓叏杩炴帴灞傜粍鎴愩€傚涓嵎绉牳鐢ㄤ簬鎻愬彇
 
 ```python
 # 杩涘叆鑴氭湰鐩綍锛岃缁傾lexNet
-bash run_standalone_train_ascend.sh [DATA_PATH] [CKPT_SAVE_PATH]
-# example: bash run_standalone_train_ascend.sh /home/DataSet/Cifar10/cifar-10-batches-bin/ /home/model/alexnet/ckpt/
+bash run_standalone_train_ascend.sh [cifar10|imagenet] [DATA_PATH] [DEVICE_ID] [CKPT_PATH]
+# example: bash run_standalone_train_ascend.sh cifar10 /home/DataSet/Cifar10/cifar-10-batches-bin/ 0 /home/model/alexnet/ckpt/
 
 # 鍒嗗竷寮忚缁傾lexNet
 
 # 杩涘叆鑴氭湰鐩綍锛岃瘎浼癆lexNet
-bash run_standalone_eval_ascend.sh [DATA_PATH] [CKPT_NAME]
-# example: bash run_standalone_eval_ascend.sh /home/DataSet/cifar10/cifar-10-verify-bin /home/model/cv/alxnet/ckpt/checkpoint_alexnet-1_1562.ckpt
+bash run_standalone_eval_ascend.sh [cifar10|imagenet] [DATA_PATH] [CKPT_NAME] [DEVICE_ID]
+# example: bash run_standalone_eval_ascend.sh cifar10 /home/DataSet/cifar10/cifar-10-verify-bin /home/model/cv/alxnet/ckpt/checkpoint_alexnet-1_1562.ckpt 0
 ```
 
 - 鍦� ModelArts 杩涜璁粌 (濡傛灉浣犳兂鍦╩odelarts涓婅繍琛岋紝鍙互鍙傝€冧互涓嬫枃妗� [modelarts](https://support.huaweicloud.com/modelarts/))
@@ -221,7 +221,7 @@ train.py鍜宑onfig.py涓富瑕佸弬鏁板涓嬶細
   ```bash
   python train.py --config_path default_config.yaml --data_path cifar-10-batches-bin --ckpt_path ckpt > log 2>&1 &
   # 鎴栬繘鍏ヨ剼鏈洰褰曪紝鎵ц鑴氭湰
-  bash run_standalone_train_ascend.sh /home/DataSet/Cifar10/cifar-10-batches-bin/ /home/model/alexnet/ckpt/
+  bash run_standalone_train_ascend.sh cifar10 /home/DataSet/Cifar10/cifar-10-batches-bin/ 0 /home/model/alexnet/ckpt/
   ```
 
   缁忚繃璁粌鍚庯紝鎹熷け鍊煎涓嬶細
@@ -243,7 +243,7 @@ train.py鍜宑onfig.py涓富瑕佸弬鏁板涓嬶細
   ```bash
   python train.py --config_path default_config.yaml --device_target "GPU" --data_path cifar-10-batches-bin --ckpt_path ckpt > log 2>&1 &
   # 鎴栬繘鍏ヨ剼鏈洰褰曪紝鎵ц鑴氭湰
-  bash run_standalone_train_for_gpu.sh cifar-10-batches-bin ckpt
+  bash run_standalone_train_gpu.sh cifar10 cifar-10-batches-bin ckpt
   ```
 
   缁忚繃璁粌鍚庯紝鎹熷け鍊煎涓嬶細
@@ -268,7 +268,7 @@ train.py鍜宑onfig.py涓富瑕佸弬鏁板涓嬶細
   ```bash
   python eval.py --config_path default_config.yaml --data_path cifar-10-verify-bin --ckpt_path ckpt/checkpoint_alexnet-1_1562.ckpt > eval_log.txt 2>&1 &
   #鎴栬繘鍏ヨ剼鏈洰褰曪紝鎵ц鑴氭湰
-  bash run_standalone_eval_ascend.sh /home/DataSet/cifar10/cifar-10-verify-bin /home/model/cv/alxnet/ckpt/checkpoint_alexnet-1_1562.ckpt
+  bash run_standalone_eval_ascend.sh cifar10 cifar-10-verify-bin ckpt/checkpoint_alexnet-1_1562.ckpt 0
   ```
 
   鍙€氳繃"eval_log鈥濇枃浠舵煡鐪嬬粨鏋溿€傛祴璇曟暟鎹泦鐨勫噯纭巼濡備笅锛�
@@ -283,7 +283,7 @@ train.py鍜宑onfig.py涓富瑕佸弬鏁板涓嬶細
   ```bash
   python eval.py --config_path default_config.yaml --device_target "GPU" --data_path cifar-10-verify-bin --ckpt_path ckpt/checkpoint_alexnet-30_1562.ckpt > eval_log 2>&1 &
   #鎴栬繘鍏ヨ剼鏈洰褰曪紝鎵ц鑴氭湰
-  bash run_standalone_eval_for_gpu.sh cifar-10-verify-bin ckpt/checkpoint_alexnet-30_1562.ckpt
+  bash run_standalone_eval_gpu.sh cifar10 cifar-10-verify-bin ckpt/checkpoint_alexnet-30_1562.ckpt 0
   ```
 
   鍙€氳繃"eval_log鈥濇枃浠舵煡鐪嬬粨鏋溿€傛祴璇曟暟鎹泦鐨勫噯纭巼濡備笅锛�
diff --git a/official/cv/resnet/README.md b/official/cv/resnet/README.md
index 4d486f93b416f5b1d6f78da2afeb0348024f7afa..20e0e9371859afefa9979c215a2e138c58ac6b71 100644
--- a/official/cv/resnet/README.md
+++ b/official/cv/resnet/README.md
@@ -167,27 +167,27 @@ If you want to run in modelarts, please check the official documentation of [mod
 
 ```python
 # run distributed training on modelarts example
-# (1) First, Perform a or b.
+# (1) Add "config_path='/path_to_code/config/resnet50_imagenet2021_config.yaml'" on the website UI interface.
+# (2) First, Perform a or b.
 #       a. Set "enable_modelarts=True" on yaml file.
 #          Set other parameters on yaml file you need.
 #       b. Add "enable_modelarts=True" on the website UI interface.
 #          Add other parameters on the website UI interface.
-# (2) Set the config directory to "config_path=/The path of config in S3/"
 # (3) Set the code directory to "/path/resnet" on the website UI interface.
 # (4) Set the startup file to "train.py" on the website UI interface.
 # (5) Set the "Dataset path" and "Output file path" and "Job log path" to your path on the website UI interface.
 # (6) Create your job.
 
 # run evaluation on modelarts example
-# (1) Copy or upload your trained model to S3 bucket.
-# (2) Perform a or b.
+# (1) Add "config_path='/path_to_code/config/resnet50_imagenet2021_config.yaml'" on the website UI interface.
+# (2) Copy or upload your trained model to S3 bucket.
+# (3) Perform a or b.
 #       a. Set "enable_modelarts=True" on yaml file.
 #          Set "checkpoint_file_path='/cache/checkpoint_path/model.ckpt'" on yaml file.
 #          Set "checkpoint_url=/The path of checkpoint in S3/" on yaml file.
 #       b. Add "enable_modelarts=True" on the website UI interface.
 #          Add "checkpoint_file_path='/cache/checkpoint_path/model.ckpt'" on the website UI interface.
 #          Add "checkpoint_url=/The path of checkpoint in S3/" on the website UI interface.
-# (3) Set the config directory to "config_path=/The path of config in S3/"
 # (4) Set the code directory to "/path/resnet" on the website UI interface.
 # (5) Set the startup file to "eval.py" on the website UI interface.
 # (6) Set the "Dataset path" and "Output file path" and "Job log path" to your path on the website UI interface.
@@ -702,7 +702,9 @@ Export on ModelArts (If you want to run in modelarts, please check the official
 
 ```python
 # Export on ModelArts
-# (1) Perform a or b.
+# (1) Add "config_path='/path_to_code/config/resnet50_imagenet2021_config.yaml'" on the website UI interface.
+# (2) Upload or copy your trained model to S3 bucket.
+# (3) Perform a or b.
 #       a. Set "enable_modelarts=True" on default_config.yaml file.
 #          Set "checkpoint_file_path='/cache/checkpoint_path/model.ckpt'" on default_config.yaml file.
 #          Set "checkpoint_url='s3://dir_to_trained_ckpt/'" on default_config.yaml file.
@@ -715,11 +717,10 @@ Export on ModelArts (If you want to run in modelarts, please check the official
 #          Add "file_name='./resnet'" on the website UI interface.
 #          Add "file_format='AIR'" on the website UI interface.
 #          Add other parameters on the website UI interface.
-# (2) Set the config_path="/path/yaml file" on the website UI interface.
-# (3) Set the code directory to "/path/resnet" on the website UI interface.
-# (4) Set the startup file to "export.py" on the website UI interface.
-# (5) Set the "Output file path" and "Job log path" to your path on the website UI interface.
-# (6) Create your job.
+# (4) Set the code directory to "/path/resnet" on the website UI interface.
+# (5) Set the startup file to "export.py" on the website UI interface.
+# (6) Set the "Output file path" and "Job log path" to your path on the website UI interface.
+# (7) Create your job.
 ```
 
 ### Infer on Ascend310
diff --git a/official/cv/resnet/README_CN.md b/official/cv/resnet/README_CN.md
index ab8b9f6cb3bed9005073b236b9217aafa63fab83..59b68742dab50f95ad6a26c31ecd8584558988e2 100644
--- a/official/cv/resnet/README_CN.md
+++ b/official/cv/resnet/README_CN.md
@@ -151,12 +151,12 @@ bash run_eval_gpu.sh [DATASET_PATH] [CHECKPOINT_PATH]  [CONFIG_PATH]
 
 ```python
 # 鍦╩odelarts涓婁娇鐢ㄥ垎甯冨紡璁粌鐨勭ず渚嬶細
-# (1) 閫夊潃a鎴栬€卋鍏朵腑涓€绉嶆柟寮忋€�
+# (1) 鍦ㄧ綉椤典笂璁剧疆 "config_path='/path_to_code/config/resnet50_imagenet2021_config.yaml'"
+# (2) 閫夊潃a鎴栬€卋鍏朵腑涓€绉嶆柟寮忋€�
 #       a. 璁剧疆 "enable_modelarts=True" 銆�
 #          鍦▂aml鏂囦欢涓婅缃綉缁滄墍闇€鐨勫弬鏁般€�
 #       b. 澧炲姞 "enable_modelarts=True" 鍙傛暟鍦╩odearts鐨勭晫闈笂銆�
 #          鍦╩odelarts鐨勭晫闈笂璁剧疆缃戠粶鎵€闇€鐨勫弬鏁般€�
-# (2) 鍦╩odelarts鐨勭晫闈笂璁剧疆閰嶇疆鏂囦欢鐨勮矾寰�"config_path=/The path of config in S3/"
 # (3) 鍦╩odelarts鐨勭晫闈笂璁剧疆浠g爜鐨勮矾寰� "/path/resnet"銆�
 # (4) 鍦╩odelarts鐨勭晫闈笂璁剧疆妯″瀷鐨勫惎鍔ㄦ枃浠� "train.py" 銆�
 # (5) 鍦╩odelarts鐨勭晫闈笂璁剧疆妯″瀷鐨勬暟鎹矾寰� "Dataset path" ,
@@ -164,20 +164,20 @@ bash run_eval_gpu.sh [DATASET_PATH] [CHECKPOINT_PATH]  [CONFIG_PATH]
 # (6) 寮€濮嬫ā鍨嬬殑璁粌銆�
 
 # 鍦╩odelarts涓婁娇鐢ㄦā鍨嬫帹鐞嗙殑绀轰緥
-# (1) 鎶婅缁冨ソ鐨勬ā鍨嬪湴鏂瑰埌妗剁殑瀵瑰簲浣嶇疆銆�
-# (2) 閫夊潃a鎴栬€卋鍏朵腑涓€绉嶆柟寮忋€�
+# (1) 鍦ㄧ綉椤典笂璁剧疆 "config_path='/path_to_code/config/resnet50_imagenet2021_config.yaml'"
+# (2) 鎶婅缁冨ソ鐨勬ā鍨嬪湴鏂瑰埌妗剁殑瀵瑰簲浣嶇疆銆�
+# (3) 閫夊潃a鎴栬€卋鍏朵腑涓€绉嶆柟寮忋€�
 #       a. 璁剧疆 "enable_modelarts=True"
 #          璁剧疆 "checkpoint_file_path='/cache/checkpoint_path/model.ckpt" 鍦� yaml 鏂囦欢.
 #          璁剧疆 "checkpoint_url=/The path of checkpoint in S3/" 鍦� yaml 鏂囦欢.
 #       b. 澧炲姞 "enable_modelarts=True" 鍙傛暟鍦╩odearts鐨勭晫闈笂銆�
 #          澧炲姞 "checkpoint_file_path='/cache/checkpoint_path/model.ckpt'" 鍙傛暟鍦╩odearts鐨勭晫闈笂銆�
 #          澧炲姞 "checkpoint_url=/The path of checkpoint in S3/" 鍙傛暟鍦╩odearts鐨勭晫闈笂銆�
-# (2) 鍦╩odelarts鐨勭晫闈笂璁剧疆閰嶇疆鏂囦欢鐨勮矾寰�"config_path=/The path of config in S3/"
-# (3) 鍦╩odelarts鐨勭晫闈笂璁剧疆浠g爜鐨勮矾寰� "/path/resnet"銆�
-# (4) 鍦╩odelarts鐨勭晫闈笂璁剧疆妯″瀷鐨勫惎鍔ㄦ枃浠� "eval.py" 銆�
-# (5) 鍦╩odelarts鐨勭晫闈笂璁剧疆妯″瀷鐨勬暟鎹矾寰� "Dataset path" ,
+# (4) 鍦╩odelarts鐨勭晫闈笂璁剧疆浠g爜鐨勮矾寰� "/path/resnet"銆�
+# (5) 鍦╩odelarts鐨勭晫闈笂璁剧疆妯″瀷鐨勫惎鍔ㄦ枃浠� "eval.py" 銆�
+# (6) 鍦╩odelarts鐨勭晫闈笂璁剧疆妯″瀷鐨勬暟鎹矾寰� "Dataset path" ,
 # 妯″瀷鐨勮緭鍑鸿矾寰�"Output file path" 鍜屾ā鍨嬬殑鏃ュ織璺緞 "Job log path" 銆�
-# (6) 寮€濮嬫ā鍨嬬殑鎺ㄧ悊銆�
+# (7) 寮€濮嬫ā鍨嬬殑鎺ㄧ悊銆�
 ```
 
 # 鑴氭湰璇存槑
@@ -667,8 +667,9 @@ python export.py --checkpoint_file_path [CKPT_PATH] --file_name [FILE_NAME] --fi
 ModelArts瀵煎嚭mindir
 
 ```python
-# (1) 鎶婅缁冨ソ鐨勬ā鍨嬪湴鏂瑰埌妗剁殑瀵瑰簲浣嶇疆銆�
-# (2) 閫夊潃a鎴栬€卋鍏朵腑涓€绉嶆柟寮忋€�
+# (1) 鍦ㄧ綉椤典笂璁剧疆 "config_path='/path_to_code/config/resnet50_imagenet2021_config.yaml'"
+# (2) 鎶婅缁冨ソ鐨勬ā鍨嬪湴鏂瑰埌妗剁殑瀵瑰簲浣嶇疆銆�
+# (3) 閫夊潃a鎴栬€卋鍏朵腑涓€绉嶆柟寮忋€�
 #       a. 璁剧疆 "enable_modelarts=True"
 #          璁剧疆 "checkpoint_file_path='/cache/checkpoint_path/model.ckpt" 鍦� yaml 鏂囦欢銆�
 #          璁剧疆 "checkpoint_url=/The path of checkpoint in S3/" 鍦� yaml 鏂囦欢銆�
@@ -679,7 +680,6 @@ ModelArts瀵煎嚭mindir
 #          澧炲姞 "checkpoint_url=/The path of checkpoint in S3/" 鍙傛暟鍦╩odearts鐨勭晫闈笂銆�
 #          璁剧疆 "file_name='./resnet'"鍙傛暟鍦╩odearts鐨勭晫闈笂銆�
 #          璁剧疆 "file_format='AIR'" 鍙傛暟鍦╩odearts鐨勭晫闈笂銆�
-# (3) 璁剧疆缃戠粶閰嶇疆鏂囦欢鐨勮矾寰� "config_path=/The path of config in S3/"
 # (4) 鍦╩odelarts鐨勭晫闈笂璁剧疆浠g爜鐨勮矾寰� "/path/resnet"銆�
 # (5) 鍦╩odelarts鐨勭晫闈笂璁剧疆妯″瀷鐨勫惎鍔ㄦ枃浠� "export.py" 銆�
 # 妯″瀷鐨勮緭鍑鸿矾寰�"Output file path" 鍜屾ā鍨嬬殑鏃ュ織璺緞 "Job log path" 銆�