diff --git a/ppcls/configs/ImageNet/ResNet/ResNet50_fp16.yaml b/ppcls/configs/ImageNet/ResNet/ResNet50_fp16.yaml
index f039a60b6d0ff9e1d0cc2f33e662c5856481bfbf..769ff361e497c41846759cc81bc31df5e692bd82 100644
--- a/ppcls/configs/ImageNet/ResNet/ResNet50_fp16.yaml
+++ b/ppcls/configs/ImageNet/ResNet/ResNet50_fp16.yaml
@@ -16,6 +16,7 @@ Global:
   save_inference_dir: ./inference
   # training model under @to_static
   to_static: False
+  use_dali: True
 
 # mixed precision training
 AMP:
diff --git a/ppcls/static/train.py b/ppcls/static/train.py
index e262f27ffdcc827414df459822f45963f3bb0f92..ae2b440526610aff9a56e92688c4c17b9227b545 100644
--- a/ppcls/static/train.py
+++ b/ppcls/static/train.py
@@ -81,14 +81,13 @@ def main(args):
     # amp related config
     if 'AMP' in config:
         AMP_RELATED_FLAGS_SETTING = {
-            'FLAGS_cudnn_exhaustive_search': "1",
-            'FLAGS_conv_workspace_size_limit': "1500",
-            'FLAGS_cudnn_batchnorm_spatial_persistent': "1",
-            'FLAGS_max_indevice_grad_add': "8",
-            "FLAGS_cudnn_batchnorm_spatial_persistent": "1",
+            'FLAGS_cudnn_exhaustive_search': 1,
+            'FLAGS_conv_workspace_size_limit': 1500,
+            'FLAGS_cudnn_batchnorm_spatial_persistent': 1,
+            'FLAGS_max_inplace_grad_add': 8,
         }
-        for k in AMP_RELATED_FLAGS_SETTING:
-            os.environ[k] = AMP_RELATED_FLAGS_SETTING[k]
+        os.environ['FLAGS_cudnn_batchnorm_spatial_persistent'] = '1'
+        paddle.fluid.set_flags(AMP_RELATED_FLAGS_SETTING)
 
     use_xpu = global_config.get("use_xpu", False)
     use_npu = global_config.get("use_npu", False)