diff --git a/model_zoo/official/cv/mobilenetv2_quant/scripts/run_train_quant.sh b/model_zoo/official/cv/mobilenetv2_quant/scripts/run_train_quant.sh
index e4d41ac9a2..c7a3d00863 100644
--- a/model_zoo/official/cv/mobilenetv2_quant/scripts/run_train_quant.sh
+++ b/model_zoo/official/cv/mobilenetv2_quant/scripts/run_train_quant.sh
@@ -75,15 +75,15 @@ run_gpu()
     python ${BASEPATH}/../train.py \
         --dataset_path=$4 \
         --device_target=$1 \
-        --quantization_aware=True \
-        &> ../train.log &  # dataset train folder
+        --pre_trained=$5 \
+        --quantization_aware=True &> ../train.log &  # dataset train folder
 }
 
-if [ $# -gt 6 ] || [ $# -lt 4 ]
+if [ $# -gt 6 ] || [ $# -lt 5 ]
 then
     echo "Usage:\n \
-          Ascend: sh run_train.sh Ascend [DEVICE_NUM] [SERVER_IP(x.x.x.x)] [VISIABLE_DEVICES(0,1,2,3,4,5,6,7)] [DATASET_PATH] [CKPT_PATH]\n \
-          GPU: sh run_train.sh GPU [DEVICE_NUM] [VISIABLE_DEVICES(0,1,2,3,4,5,6,7)] [DATASET_PATH]\n \
+          Ascend: sh run_train_quant.sh Ascend [DEVICE_NUM] [SERVER_IP(x.x.x.x)] [VISIABLE_DEVICES(0,1,2,3,4,5,6,7)] [DATASET_PATH] [CKPT_PATH]\n \
+          GPU: sh run_train_quant.sh GPU [DEVICE_NUM] [VISIABLE_DEVICES(0,1,2,3,4,5,6,7)] [DATASET_PATH] [CKPT_PATH]\n \
           "
 exit 1
 fi
diff --git a/model_zoo/official/cv/mobilenetv2_quant/src/dataset.py b/model_zoo/official/cv/mobilenetv2_quant/src/dataset.py
index 105a5e1396..ce9f2d8faf 100644
--- a/model_zoo/official/cv/mobilenetv2_quant/src/dataset.py
+++ b/model_zoo/official/cv/mobilenetv2_quant/src/dataset.py
@@ -22,7 +22,6 @@ import mindspore.dataset.engine as de
 import mindspore.dataset.transforms.vision.c_transforms as C
 import mindspore.dataset.transforms.c_transforms as C2
 import mindspore.dataset.transforms.vision.py_transforms as P
-from src.config import config_ascend
 
 
 def create_dataset(dataset_path, do_train, config, device_target, repeat_num=1, batch_size=32):
@@ -42,7 +41,7 @@ def create_dataset(dataset_path, do_train, config, device_target, repeat_num=1,
         rank_size = int(os.getenv("RANK_SIZE"))
         rank_id = int(os.getenv("RANK_ID"))
         columns_list = ['image', 'label']
-        if config_ascend.data_load_mode == "mindrecord":
+        if config.data_load_mode == "mindrecord":
             load_func = partial(de.MindDataset, dataset_path, columns_list)
         else:
             load_func = partial(de.ImageFolderDatasetV2, dataset_path)
@@ -54,6 +53,13 @@ def create_dataset(dataset_path, do_train, config, device_target, repeat_num=1,
                                num_shards=rank_size, shard_id=rank_id)
         else:
             ds = load_func(num_parallel_workers=8, shuffle=False)
+    elif device_target == "GPU":
+        if do_train:
+            from mindspore.communication.management import get_rank, get_group_size
+            ds = de.ImageFolderDatasetV2(dataset_path, num_parallel_workers=8, shuffle=True,
+                                         num_shards=get_group_size(), shard_id=get_rank())
+        else:
+            ds = de.ImageFolderDatasetV2(dataset_path, num_parallel_workers=8, shuffle=True)
     else:
         raise ValueError("Unsupport device_target.")
 
diff --git a/model_zoo/official/cv/mobilenetv2_quant/train.py b/model_zoo/official/cv/mobilenetv2_quant/train.py
index 2253fbb5a0..bd8051cccc 100644
--- a/model_zoo/official/cv/mobilenetv2_quant/train.py
+++ b/model_zoo/official/cv/mobilenetv2_quant/train.py
@@ -56,7 +56,7 @@ if args_opt.device_target == "Ascend":
     context.set_context(mode=context.GRAPH_MODE,
                         device_target="Ascend",
                         device_id=device_id, save_graphs=False)
-elif args_opt.platform == "GPU":
+elif args_opt.device_target == "GPU":
     init("nccl")
     context.set_auto_parallel_context(device_num=get_group_size(),
                                       parallel_mode=ParallelMode.DATA_PARALLEL,
@@ -205,5 +205,5 @@ def train_on_gpu():
 if __name__ == '__main__':
     if args_opt.device_target == "Ascend":
         train_on_ascend()
-    elif args_opt.platform == "GPU":
+    elif args_opt.device_target == "GPU":
         train_on_gpu()