diff --git a/examples/stable_diffusion_xl/gm/modules/transformers/transformers.py b/examples/stable_diffusion_xl/gm/modules/transformers/transformers.py
index d172199b65..99aedae576 100644
--- a/examples/stable_diffusion_xl/gm/modules/transformers/transformers.py
+++ b/examples/stable_diffusion_xl/gm/modules/transformers/transformers.py
@@ -10,7 +10,8 @@
 
 def scaled_dot_product_attention(query, key, value, attn_mask=None, dtype=None):
     # force fp16 precision calculation
-    _dtype = query.dtype
+    origin_dtype = query.dtype
+    dtype = origin_dtype if dtype is None else dtype
     if dtype is not None:
         query, key, value = query.astype(dtype), key.astype(dtype), value.astype(dtype)
 
@@ -19,14 +20,14 @@ def scaled_dot_product_attention(query, key, value, attn_mask=None, dtype=None):
         attn_weight = ops.softmax(
             ops.cast(ops.matmul(query, key.swapaxes(-2, -1)) / (query.shape[-1] ** 0.5) + attn_mask, ms.float32),
             axis=-1,
-        ).astype(_dtype)
+        ).astype(dtype)
     else:
         attn_weight = ops.softmax(
             ops.cast(ops.matmul(query, key.swapaxes(-2, -1)) / (query.shape[-1] ** 0.5), ms.float32), axis=-1
-        ).astype(_dtype)
+        ).astype(dtype)
 
     out = ops.matmul(attn_weight, value)
-    out = out.astype(_dtype)
+    out = out.astype(origin_dtype)
 
     return out