diff --git a/mindone/transformers/mindspore_adapter/amp.py b/mindone/transformers/mindspore_adapter/amp.py
index b950a2332..ea7eb0323 100644
--- a/mindone/transformers/mindspore_adapter/amp.py
+++ b/mindone/transformers/mindspore_adapter/amp.py
@@ -1,6 +1,25 @@
 import mindspore as ms
 from mindspore import nn
-from mindspore.train.amp import AMP_BLACK_LIST, _auto_black_list
+from mindspore.train.amp import _auto_black_list
+
+HALF_UNFRIENDLY_LAYERS = [
+    nn.BatchNorm1d,
+    nn.BatchNorm2d,
+    nn.BatchNorm3d,
+    nn.LayerNorm,
+    nn.GroupNorm,
+    nn.SiLU,
+    nn.GELU,
+    nn.Softmax,
+    nn.Sigmoid,
+    nn.MaxPool1d,
+    nn.MaxPool2d,
+    nn.MaxPool3d,
+    nn.AvgPool1d,
+    nn.AvgPool2d,
+    nn.AvgPool3d,
+    nn.CrossEntropyLoss,
+]
 
 
 def auto_mixed_precision(network, amp_level="O0", dtype=ms.float16):
@@ -33,25 +52,7 @@ def auto_mixed_precision(network, amp_level="O0", dtype=ms.float16):
     elif amp_level == "O1":
         raise NotImplementedError
     elif amp_level == "O2":
-        _auto_black_list(
-            network,
-            AMP_BLACK_LIST
-            + [
-                nn.GroupNorm,
-                nn.SiLU,
-                nn.GELU,
-                nn.Softmax,
-                nn.Sigmoid,
-                nn.MaxPool1d,
-                nn.MaxPool2d,
-                nn.MaxPool3d,
-                nn.AvgPool1d,
-                nn.AvgPool2d,
-                nn.AvgPool3d,
-                nn.CrossEntropyLoss,
-            ],
-            dtype,
-        )
+        _auto_black_list(network, HALF_UNFRIENDLY_LAYERS, dtype)
     elif amp_level == "O3":
         network.to_float(dtype)
     else: